Objective To analyze the global registration status of brain-computer interface (BCI) clinical trials and provide data to support further clinical research of this technology. Methods Clinical trial registration data related to BCI were collected from ClinicalTrials.gov, and a bibliometric approach was applied to analyze trends across registration numbers, annual changes, geographic distribution and international collaboration, sponsor types and distribution, study types and recruitment status, and indications and their characteristics. Results As of October 2024, a total of 194 BCI-related clinical trials were registered globally, showing an overall upward trend in registration numbers. The United States led with 80 trials, while no other country surpassed 20; only three trials involved international collaboration. Sponsors were predominantly universities and research institutions (48.7%), with the United States having the largest number of sponsors. Nearly 90% (88.1%) of these trials were interventional studies, approximately 40% were completed, and nearly 30% recruited fewer than 10 participants. Almost all trials have no gender restrictions on participant recruitment and include adults. BCI clinical trials primarily focused on rehabilitation and treatment of neurological disorders, with primary indications including stroke, spinal cord injury, amyotrophic lateral sclerosis, and tetraplegia. Conclusion The global clinical research activity in BCI technology is steadily increasing, demonstrating significant application potential.

Objective To analyze clinical trial data in the field of tissue engineering and regenerative medicine from ClinicalTrials.gov and the Chinese Clinical Trial Registry (ChiCTR) to present the global and Chinese competitive landscape. Methods Data on clinical trials in the field of tissue engineering and regenerative medicine were collected from the two databases. A bibliometric analysis was conducted based on the number of registrations, countries or cities, clinical trial institutions, and sponsors. Results Based on ClinicalTrials.gov data, there were 582 registered clinical trials globally in the field of tissue engineering and regenerative medicine. Among 60 countries, the United States had 233 trials, China had 71, and all other countries had fewer than 30. Among more than 2,000 clinical trial institutions, institutions such as Columbia University and UCLA in the U.S. stood out. Among 305 sponsors, 55.74% were universities/hospitals, and 27.54% were enterprises. U.S. sponsors conducted 269 clinical trials, showing high activity. Based on ChiCTR data, China registered 97 clinical trials in this field. Among 29 cities, Shanghai registered 40 trials, Beijing registered 26, and other cities registered fewer than 10 trials. Among 76 clinical trial institutions and 45 sponsors, Beijing and Shanghai had the largest numbers, with institutions like Shanghai Ninth People's Hospital and Peking University School of Stomatology being highly involved. Conclusion The number of registered clinical trials in the field of tissue engineering and regenerative medicine is on the rise globally and in China. The U.S. remains in a leading position, while China still has a gap to close with the U.S. International multicenter cooperation needs to be strengthened.

Objective To analyze the disciplinary and knowledge composition as well as the trends in brain-computer interface (BCI) research to provide insights for team development, talent cultivation, and cross-disciplinary collaboration in the field. Methods Citation analysis from bibliometrics was applied to calculate interdisciplinary indices within the field, and trend assessments were conducted through statistical analysis. Results The disciplinary diversity in BCI research continues to grow, with varying levels of knowledge concentration across disciplines. Medicine, computer science, psychology, engineering, and physiology are the primary contributing fields. Among them, the shares of medicine and psychology have decreased, while computer science has significantly increased in proportion, with humanities and social sciences contributing less frequently. Conclusion Driven by advancements in areas such as artificial intelligence, BCI research has shifted from fundamental mechanistic studies to a focus on technology development and algorithmic iteration. At this stage, computer science and engineering have emerged as key pillars in the interdisciplinary knowledge framework. In the future, as technology progresses toward clinical transformation and commercialization, clinical sciences and sociology may receive greater attention.

In the modern medical field, Radio-frequency Ultrasonic Scalpel has become an important energy instrument in minimally invasive surgery due to its ability to simultaneously output both radiofrequency and ultrasound energy, minimal damage, and fast postoperative recovery. At present, Radio-frequency Ultrasonic Scalpel is widely used, but there are few relevant reviews in China. This article summarizes the structure and principle，the current application scenarios and innovation directions of Radio-frequency Ultrasonic Scalpel, conducts a reasonable analysis of the prospects of Radio-frequency Ultrasonic Scalpel, and proposes some improvement suggestions in order to provide reference for the subsequent development of Radio-frequency Ultrasonic Scalpel.

Objective Investigating the dosimetric impact of setup errors on target volumes and organs at risk in lung cancer patients undergoing intensity-modulated radiotherapy (IMRT) guided by cone-beam CT (CBCT). Methods The study involved 35 lung cancer patients who underwent IMRT at the Beijing Chest Hospital of Capital Medical University. A total of 175 cone-beam CT (CBCT) data sets were collected. The average setup errors in the X (left-right), Y (cranio-caudal), and Z (superior-inferior) directions were calculated for each patient. These average values were then used to generate simulated plans at the treatment center. The dosimetric data obtained, including target volumes and organs at risk, were compared with the original plans to investigate the impact of setup errors on the dosimetry of intensity-modulated radiotherapy for lung cancer. Results The setup errors in the X, Y, and Z directions were (-0.17±2.67) mm, (0.80±3.39) mm, and (-0.13±2.23) mm, respectively. Among these, the Y-direction setup error had the highest proportion exceeding 5 mm, reaching 17%. When comparing the original plans with the simulated plans, the PTV D98, D95, and D2 of the target area are (98.66±0.52)%, (100.29±0.43)%, and (106.71±0.71)%, respectively, compared to (89.84±1.82)%, (96.50±1.06)%, and (107.33±0.74)%, with statistically significant differences (P<0.001). For organs at risk, the spinal cord D1CC and Dmax increased compared to the original plan, with statistically significant differences (P＜0.05). However, there were no statistically significant differences observed in dosimetric parameters for other organs at risk, including the heart (V30, V40, Dmean), lungs (V5, V20, Dmean), esophagus (V30, V50, Dmean), and left anterior descending coronary artery (LAD), when comparing the simulated plans with the original plans. Conclusion The use of CBCT can measure setup errors in lung cancer intensity-modulated radiotherapy. Setup errors can have a dosimetric impact on the actual radiotherapy plan. In clinical practice, adjustments can be made promptly based on the measured errors from CBCT to reduce setup errors and minimize their impact on the actual radiotherapy plan.

Objective To construct a specialized database for cardiovascular diseases based on multimodal diagnosis and treatment data, improve the efficiency of clinical data utilization, and assist the analysis and application of specialized disease data in cardiovascular medicine. Methods By using Hadoop based big data and artificial intelligence technologies such as NLP and CV, multimodal data in cardiovascular medicine is aggregated and managed, and a specialized disease database function is developed to provide data support services. Results The cardiovascular disease specialty database integrates over 1.2 million patient data from 1999 to present, including over 64.11 million drug orders, over 13.89 million outpatient medical records, over 750000 admission records, over 200 million test records, over 7.63 million examination records, and over 1.23 million physical examination reports. Promoting the construction and application of a specialized cardiovascular disease database has improved clinical research methods and application levels, and increased the efficiency of clinical data application from 20% to over 90%, with significant results. Up to now, 8 SCI papers have been published based on this specialized disease database, and 6 academic reports have been presented both domestically and internationally. Conclusion The cardiovascular disease specialized database based on multimodal diagnosis and treatment data has improved the diagnosis and treatment level and scientific research output of the department, playing a positive role in its application.

Objective To construct a multidimensional, subjective and objective evaluation index system for digital pathology slice scanners, providing theoretical basis for the evaluation of digital pathology slice scanners by medical institution users and managers. Methods This article developed a draft evaluation index system for digital pathology section scanners through literature analysis, enterprise discussions, group discussions, clinical research, and other methods. The Delphi method was used to determine the indicators at each level, and the Analytic Hierarchy Process was used to obtain the normalized weights of the indicators at each level and the combined weights of the secondary indicators. Results Through consistency testing of single ranking and overall ranking of indicators at all levels, this paper ultimately constructed an evaluation index system for digital pathology section scanners, including 5 dimensions and 22 secondary indicators. Conclusion The evaluation index system for digital pathology section scanners constructed in this article has good expert enthusiasm, strong participation, and high authority, which can provide a scientific theoretical basis for medical institutions to regularly conduct clinical application evaluations of digital pathology section scanners at home and abroad.

Objective This study aims to construct a biobank information management system involving multiple centers and users, with the goal of providing innovative ideas and methods for the future development of biobanks. Methods/Process In accordance with the standards and regulations of the biobank, the system adopts a technical architecture that includes a foundation layer, data layer, application layer, and user layer. It interfaces with multiple hospital information systems to achieve information interconnectivity and interoperability. It deploys several functional modules such as sample lifecycle management, storage space, equipment and consumables, sharing platform, and mobile applications, ensuring that sample information management and application are convenient, efficient, complete, secure, and traceable. Results After implementing the system, the time required for the intake of non-tissue samples, tissue samples, and the recording of informed consent forms was significantly reduced by 35%, 30%, and 62%, respectively, all of which were statistically significant (P<0.05). Furthermore, the volume of sample distribution increased by 22.3%, and the efficiency and scope of sample sharing were also significantly enhanced. Conclusion The establishment and application of the biobank information management system not only improved the efficiency and quality of sample management but also promoted the sharing and utilization of sample resources, providing strong support for biomedical research.

This study investigated the control system principles and the working mechanism of the programmable logic controller (PLC) in the HMD-IB radiotherapy simulator at our hospital. Through the examination of several cases involving typical motion system faults under PLC control, our study discussed maintenance methods and techniques employed to resolve such faults. The findings underline the importance of careful observation of motion system faults, clear analysis, accurate diagnosis of faults, and swift restoration to normal operation. All these not only minimize repair time and costs but also ensure the smooth progress of radiotherapy. Additionally, the current study provides reference insights for fellow engineers handling motion system faults in PLC-controlled systems. It also presents a preliminary exploration of how medical engineers can adapt to the maintenance of intelligent medical devices in light of new technological advancements.

Objective To construct a comprehensive digital intelligent management system for pulmonary function test, aiming to optimize patient examination processes, reduce manual data entry time, enhance clinical diagnostic and treatment efficiency, and achieve data resource sharing and equipment efficiency optimization. Methods This study conducted an in-depth analysis of the existing issues in the pulmonary function test workflow, and integrated information technology and artificial intelligence technology in line with clinical business needs and patient diagnostic requirements. A pulmonary function test system was developed using JAVA language and Oracle database, based on a B/S architecture with Tomcat and Nginx, realizing the digital and intelligent management of pulmonary function test. The study designated data from one year prior to the system launch (June 2021 to May 2022) as the control group and data from one year after the system's stable operation (June 2023 to May 2024) as the experimental group. Statistical analysis was performed by comparing indicators such as patient appointment waiting time, examination time, operating costs, annual return on investment, and equipment utilization rate to comprehensively evaluate the application effects of the pulmonary function test system. Results The experimental group experienced a reduction of 2.15 days in appointment waiting time, 27.05 minutes in check-up waiting time, and 10.89 minutes in examination time (P<0.001). Furthermore, the annual operating cost of the equipment was decreased by 24,700 yuan (P=0.037), the annual recovery rate increased by 71.06% (P=0.029), and the equipment utilization rate improved by 9.34% (P=0.044). Conclusion The comprehensive digital intelligent management system for pulmonary function test significantly optimized the examination process, enhanced equipment efficiency, and facilitated the sharing of examination results and clinical data application, which is of great importance for improving the quality and efficiency of medical services.

Objective To explore the establishment of information, intelligent, traceable management mode, effectively solve the problems in the management of hemp drugs. Methods By means of two-dimensional code technology, process reconstruction and information integration, intelligent management terminals of anesthetic drugs were fully deployed in drug warehouses, pharmacies and operating rooms with intelligent medicine cabinets as information media, and the information of anesthesiology department, HIS system, hand anesthesia system, medical technology workstation and pharmacy workstation was connected to realize traceability and closed-loop management of the whole process of anesthetic drugs. Results After the implementation of the program, the time of anesthesiologists receiving/returning drugs, the time of anesthesiologists administering anesthetic drugs, and the time of tracing a single drug were significantly lower than those in the traditional group, and the differences were statistically significant (P < 0.05). The satisfaction of anesthesiologists was increased from (86.47±6.34) to (94.11±5.65), with statistical significance (P<0.05). Conclusion The management mode of anesthetic drugs based on two-dimensional code technology and intelligent cabinet is convenient and efficient, which can improve the level of fine management and safe use of anesthetic drugs, and improve the satisfaction of anesthesiologists on the management of anesthetic drugs, and has certain promotion value.

Due to the complex operating environment of medical equipment, there are many interference factors in the operating status data, which affect the accuracy of equipment status monitoring. Therefore, a monitoring method for abnormal operation status of medical equipment based on multi-source data analysis is proposed. Using sensors to collect operational data from multiple sources of medical equipment, first calculate the soft threshold of operational status and determine the fluctuation range of operational status data. Next, use the correlation matrix to fuse the operational status data of multi-source medical equipment. Based on the results of data fusion, extract time-domain and frequency-domain features of the data, establish data feature vectors, and achieve feature mining of the data state. Then, by calculating the characteristic entropy value and operating state value of the running state data, it is determined whether the device is in an abnormal state. Finally, calculate the ratio of abnormal states of medical equipment to classify different types of abnormal states. The experimental results show that the average false alarm rate of this method in practical applications is 3.25%, demonstrating high monitoring accuracy; Can effectively improve monitoring accuracy and reduce false alarm rates.

Objective This study visualizes the past decade of research on resting-state functional magnetic resonance imaging (rs-fMRI), highlighting key trends and emerging topics. Methods English rs-fMRI literature from 2014 to 2023 were retrieved from the Web of Science Core Collection. VOSviewer and CiteSpace software were used to analyze and map the data. Results A total of 10,581 articles were analyzed, showing a steady increase in publications. China has the highest number of publications (4836 papers), while the United States has the highest number of citations (111,945 citations). Capital Medical University and Gong Qiyong were the top institution and author, respectively. 《Frontiers in Neuroscience》 published the most articles. Frequent keywords included functional connectivity, default mode network, and brain network, with recent trends focusing on machine learning and cognitive function. Conclusions In recent years, Interest in rs-fMRI research is growing. Analytical methods have transitioned from traditional techniques like functional connectivity to innovative approaches such as degree centrality and dynamic functional connectivity. The focus has shifted from neuroimaging features in brain diseases to the integration of imaging and artificial intelligence for accurate diagnosis and classification. Future studies will likely emphasize optimizing data analysis methods and expanding the applications of machine learning technologies.

Nanosecond pulsed electric field (nsPEF) is an emerging ablation technology that induces tumor cell electroporation, calcium influx, and reactive oxygen species (ROS) accumulation by applying a high-intensity electric field in an extremely short duration. This review outlines the mechanisms of nsPEF in tumor ablation, particularly its specific effects at the cellular and molecular levels. Research indicates that nsPEF induces tumor cell death through various pathways, including intrinsic and extrinsic apoptosis, necrosis and necroptosis, autophagy, and immune response pathways, thereby enhancing anti-tumor immune reactions. Despite the promising potential of nsPEF in tumor treatment, its application faces challenges such as the need for further elucidation of its mechanisms, optimization of parameters, and improvement of treatment strategies. Future research should continue to explore the application of nsPEF in different types of tumors and integrate it with other treatment modalities to develop more comprehensive and personalized therapeutic approaches, thereby enhancing its clinical efficacy and safety.

Wound healing is a complex and dynamic physiological process involving multiple stages of biological responses, including hemostasis, inflammation, proliferation, and remodeling. In recent years, nanosecond pulsed electric fields (nsPEF) have garnered significant attention for their potential in cellular and tissue repair, demonstrating promising applications in promoting wound healing. This review systematically summarizes the fundamental principles of nsPEF and its mechanisms of influence during the wound healing process, exploring its effects on cell proliferation, migration, angiogenesis, and anti-inflammatory and antibacterial actions, as well as its ability to enhance the uptake of drugs and nutrients through electroporation.Research indicates that nsPEF can effectively promote the proliferation and migration of fibroblasts and keratinocytes, enhance the formation of new blood vessels, and reduce local inflammatory responses. Additionally, nsPEF can support tissue regeneration by inducing electroporation in cell membranes, thereby increasing cellular uptake of drugs and signaling molecules. These biological effects collectively accelerate the wound healing process. Although nsPEF is still in the exploratory stage of clinical application, preliminary results from animal models and clinical trials have shown that it can significantly accelerate the healing of acute and chronic wounds while reducing infection rates. However, further research is needed to address questions regarding the effects of different intensities, frequencies, and durations of electric field exposure on treatment outcomes, as well as the applicability to various wound types and long-term safety. Future studies should focus on optimizing the parameters for nsPEF use and combining it with other treatment methods to achieve personalized treatment plans, thereby improving overall efficacy and safety.

Objective Conduct a study on the application of AI for identifying Ruedi-Augower II type Pilon fractures using DICOM format CT data, with an emphasis on evaluating the accuracy of AI software in fracture identification and localization. Methods A retrospective analysis was performed on 20 patients diagnosed with Ruedi-Augower II type Pilon fractures between January 2020 and August 2024, comprising 11 left ankles and 9 right ankles, categorized into 5 AO-B type and 15 C type fractures, with a demographic distribution of 12 males and 8 females aged from 14 to 68 years. The data were systematically randomized and subsequently reviewed by a senior orthopedic surgeon utilizing the hospital's imaging system to identify the displaced fracture fragments in each case, assigning unique identifiers accordingly. Measurements were taken for the displacements along the X (lateral-medial), Y (antero-posterior), and Z (superior-inferior) axes as well as the rotational angles of each fragment. Following this, the data were sequentially imported into an AI recognition software developed by our team, which was analyzed by a junior orthopedic surgeon using said software. The program automatically quantified the number of fracture points per case while generating a three-dimensional model of the tibia for interactive segmentation of displaced fragments. After confirmation by two senior orthopedic surgeons that these segments aligned with those identified manually, simulated reduction procedures commenced. Upon completion of these reductions, the software autonomously calculated displacements across X (lateral-medial), Y (antero-posterior), and Z (superior-inferior) axes alongside rotational angles for each fragment; ultimately producing a comprehensive report detailing all displacement metrics for fracture fragments along with counts of fracture points and classification information. Results In the analysis of 20 cases, the software identified 19 as AO-C type and 1 as AO-B type, resulting in a fracture classification accuracy of 70%. Both the manual group and the software group demonstrated consistent segmentation of fracture blocks, with each case yielding at least two joint surface bone blocks, totaling 63 fracture blocks overall. Statistical analysis revealed no significant differences in measurements of displacement along the X, Y, and Z axes or rotational angles between the two groups (P>0.05), indicating good consistency between the two measurement methods. Conclusion The AI recognition software is capable of measuring the displacement information of Ruedi-Augower II type Pilon fractures with an efficacy equivalent to that of manual measurements, thereby confirming the software's precision in identifying and localizing fractures. This innovative approach, which employs simulation techniques to accurately ascertain the spatial coordinates of bone fragments, provides valuable guidance for preoperative planning of reduction strategies.

Objective Diffusion correlation tomography (DCT) can detect blood flow changes induced by early tissue disease. As the tomographic imaging device, large-area contact DCT equipment requires a large-scale source detector (S-D) array to complete data acquisition, resulting in high equipment costs. Methods To address this issue, this article proposes using an optical switch array to time-division multiplex one S-D group into eight groups, covering a total of 8×8 cm2 of target tissue. The S-D cross distribution of long and short distances in each group forms a concentric circular structure. By utilizing its symmetry and equivalence, the balance of photons obtained by each voxel is ensured, and the detection area and depth is expanded. Results Based on this low-cost DCT device, the reconstruction position of the cross-shape phantom anomaly is accurate, and the morphology is almost complete. The contrast of the second reconstructed slice (0.5-1 cm depth) is 0.75. The contrast of the tubular anomaly is well proportional to the flow rate, and the reconstruction position is accurate, the shape is complete. In the cuff compression clinical test, the blood flow index in the relaxed state is about 10 times that of the compression state. The 3D reconstructed image and its standard deviation also indicates that the blood flow in the relaxed state is more abundant. Conclusion By the time-division multiplexing function of the optical switch, the cost of this contact DCT device with large detection area has been effectively reduced by 60%, and the detection depth is almost 1.5 cm. The experimental results also indicate that this contact DCT device has powerful detection ability for different morphological abnormalities, and can be used as a new detection method to detect diseases related to abnormal blood flow perfusion.

Objective To detect the continuity of three modules in the software by using TQA tool of Tomotherapy, and to observe and analyze the stability of dynamic Jaw. MethodsThe data required for the three TQA modules were collected using the Radixact detector and ionization chamber, field width constancy (FWC) and Maximum Jaw Encoder Error (MJEE) were used to observe the field width constancy (J01 and J07) and dynamic Jaw constancy in Daily QA module ;In the Field Width-Dynamic JAWS module, the Gamma Index Maximum (GIM) and the Field Width Percent Difference (FWPD) are used to measure the stability of four fields (J42, J20, J14, J07) in symmetric and asymmetric conditions ;The Time Skew (TS) and Relative Jaw fluence output factor (RJFOF) were calculated in Jaw Sweep-Dynamic Jaws module to observe the field width stability, Dynamic lead gate Time accuracy, Dynamic Jaw scanning stability and Dynamic lead gate speed accuracy. Results The average FWC of J01 in the Daily QA module is 98.88% ± 0.67%, which is within the normal range of 95-105 and shows a relatively stable state. The average FWC of J07 is 99.75% ± 0.17%, which is within the normal range of 98-102. The fluctuation range of MJEE of the front and back jaw doors over time is -0.3 to 0.2, with an average value of micrometers, indicating that the motion error of the front and back jaw is very small. The ten states of four different jaw widths in the Field Width Dynamic Jaws module vary over time. The GIM of FW is within the normal tolerance range of 0-1, and the FWPD is also within the tolerance range of -1 to 1 over time. The fluctuation of jaw width over time is relatively small. The jaw reaction speed in the Jaw Sweep Dynamic Jaws module remains stable over time, with an average of -0.006 seconds ± 0.003 seconds. The average values of RJFOF J20, RJFOF J14, and RJFOF J07 are 0.999757 ± 0.000557, 0.999844 ± 0.000662, and 0.998641 ± 0.001008, respectively, indicating that there is almost no change in the output factor values of the injection volume. The corresponding field widths in the three modules are within the tolerance range, with precision errors in the micrometer level. The jaw response time is extremely short, and the RJFOF value is close to the ideal value of 1. Conclusion Through the analysis of one-year data of three modules, the dynamic Jaw is stable with time.

Objective To reveals the research trends and vital topics in the field of medical engineering by conducting a bibliometric analysis on the historical literature data. Methods The PubMed database and the Medpulse bibliometric analysis platform were used to retrieve medical engineering research literature published from 2014 to 2024. The retrieved literature was subjected to data mining using the R package 'bibliometrix' (version 4.2.3). Results A total of 3,279 medical-engineering-related papers were retrieved, cited 2,589 times in total, with the peak publication year being 2023, which saw 442 articles published. The journal HELIYON featured the most articles on the subject, with a total of 138 publications. The two most prolific authors are from the United States and China. The top three research institutions by publication volume are all located in the United States. Both the United States and China have actively participated in international collaborations in the field of medical engineering. Key research themes over the past decade include “Biomedical Engineering” “Tissue Engineering” and “Drug Delivery”. The topics of high impact factor articles are relatively concentrated, while the topics of highly cited articles are diverse. Conclusion This study provides a comprehensive analysis of the hot topics and development trends in the field of medical engineering over the past decade, offering a solid foundation for professionals to understand their positioning and select research topics.

Objective To improve the in-hospital procurement process of orthopaedic consumables, to better complete the task of quantity procurement, to achieve fine management of orthopaedic consumables, and to promote the high-quality development of public hospitals. Methods Based on SPD system, the information island of each department was opened up, process reengineering was promoted, and the integrated whole process management of orthopedics was formed, and the task of contract group was completed with information tools. Results The standardization of orthopedic implant management was significantly improved, the satisfaction of patients was significantly improved, the accuracy of disinfection kits in disinfection and supply room was significantly improved, and the statistical time of set tape volume was significantly shortened, with statistical significance (P < 0.05). Conclusion The application of SPD system can improve the management efficiency of hospital, reduce the operating cost of hospital, ensure the smooth implementation of volume procurement, and provide data support for hospital managers to make scientific decisions.

Assisted medical diagnosis has become an important research direction in deep learning. Based on multi-layer neural networks, non-linear mapping between input and specific output can be achieved by extracting shallow features of combined data, especially in capturing lesion area features and revealing details that are difficult to observe with the naked eye. This article mainly focuses on the application of deep learning networks in the precise automatic classification of gastric cancer, the relationship between deep features and genes, and prognosis evaluation, with a focus on sorting out the basic ideas and improvement points of the model; Providing new perspectives and methods for computer-aided diagnosis has brought different entry points for accurate diagnosis and personalized treatment of patients.

With a history for more than 200 years, blood gas analysis has been widely used in clinical medicine. Currently, the commonly used methods for blood gas analysis are invasive detection technology. Although the technology is extensively employed, there are also many problems, such as infection, bleeding due to the invasive operation and discontinuous mointroing. Therefore, a number of non-invasive blood gas monitoring technologies have gradually emerged to make up for the shortcomings. In this paper, we reviewed the development history of blood gas analysis technology in detail, and we also discussed the development of non-invasive blood gas analysis technology. With a special attention to the application of optical Cavity Ring-Down Spectroscopy (CRDS) in non-invasive blood gas analysis and monitoring technology, we believe this is a direction for the future development of non-invasive blood gas technology.

Objective This study aims to analyze the operating costs of laboratory department by constructing a cost model for laboratory tests, so as to achieve more effective cost control and resource optimization. Methods The operating data of the immunology group and biochemistry group of the laboratory department were collected, including the income and reagent cost of each kind of test, and the total income, theoretical cost rate, actual cost rate, non-profit cost rate, and the deviation between the theoretical and actual cost rates were calculated. The cost structure of two groups of test projects through the correlation between deviation and non-measured cost rate was analyzed. Results The actual and theoretical cost rates of the biochemical group were significantly lower than 40%, and the actual cost rate of the immune group was higher than 40%, but there was no significant difference between the theoretical cost rate and 40%. The high cost was mainly caused by the increase of quality control and calibration costs in the biochemical group. It could be improved by reducing the frequency of reagent batch replacement. In biochemistry group, the high cost is mainly caused by additional depletion of reagents and the imprecision of the theoretical cost rate measurement. The number of theoretical tests of reagents should be carefully evaluated. Conclusion The application of cost accounting model is not only helpful to identify and analyze the cost structure of laboratory tests, but also provides an important reference for further optimizing resource allocation and improving operational efficiency of the laboratory department.

Objective To solve the problem of low maintenance quality and efficiency in traditional modes, provide an online digital platform for operation training and troubleshooting of various medical equipment, and improve the quality and efficiency of medical equipment maintenance. Methods Adopting front-end and back-end separation technology, building a technical support auxiliary system for medical equipment training, troubleshooting, and quality control based on Python-Django framework and VUE framework. The system supports mobile phone usage and can be used as a medical device teaching system. It also has evaluation and feedback functions, which can dynamically optimize technical guidance solutions. Results After the system trial operation, the average daily number of equipment repairs increased from 7.53 to 9.43, and the average daily fault repair rate increased from 78% to 86%, with statistical significance (P<0.05). Conclusion this system has the characteristics of medical equipment composition in our hospital. By digitizing technical support data and providing professional guidance through a digital platform, it can help improve the level of maintenance management. It is called an iteratively updated "maintenance knowledge base".

Transcranial magnetic stimulator is a noninvasive neuromodulation device, which has been widely used in many fields such as psychiatry and neurology, but prolonged operation is prone to lead to its failure. This paper describes three cases of Magneuro 100 transcranial magnetic stimulator failure. The first case is overheating alarm, first analyze the heat dissipation mechanism, determine the heat dissipation fan is damaged, replace the problem solved. The second case is capacitor voltage abnormality, by analyzing the charging principle of the high-voltage storage capacitor, disassembling the machine and testing the key electronic components, and found that the insulated gate bipolar transistor was damaged, and the problem was solved after replacement. The third case is the failure of the motor evoked potential monitoring module, EMG can not be displayed, after the signal acquisition and transmission path inspection, found that the synchronization interface and the circuit board of the weld joints loose, re-welded after the problem is solved. This paper can help equipment engineers to master the structural principles and troubleshooting methods of similar equipment to protect the continuity and safety of hospital work.

Objective Visual analysis tools were used to explore and summarize the research status, hot spots and trends of SPD management mode in medical consumables. Methods With the core database of China National Knowledge Network (CNKI) as the literature data source and the literature published so far in the field of SPD management mode as the main analysis object, the CiteSpace 6.3.R1 software was used to analyze the literature publication trend, authors, research institutions and keywords in this field, and the related visual maps were drawn. Results The relevant academic achievements were first published in 2016, and the number of papers has been on the rise in recent years. Most of the research institutions are concentrated in the southern region, while the research institutions in the northern region are relatively few. The highest frequency of occurrence is "medical supplies" (89 times), "fine management" (45 times),"medical supplies management" (19 times), and the central value of such keywords is also high. The research on the SPD distribution model for medical consumables in China began in 2016, which is relatively late. From 016 to 2019 was the initial stage of the SPD distribution model, mainly focusing on the changes in hospital logistics management, and replacing the methods of entry and exit from the warehouse, acceptance, and requisition through the SPD model. In recent years, hospitals have begun to pay attention to the refined of medical consumables, including automatic reordering, real-time tracking, and rapid response, and gradually extended from management to management plus supervision. For medical institutions with campuses, the SPD model helps to reduce duplicate construction. Conclusion The SPD model has great potential in optimizing medical material management and improving hospital operational efficiency while ensuring data security.

Chronic liver disease is one of the major chronic diseases in China, and slowing or even reversing its course is a significant challenge. The sympathetic nervous system has an important role in the development of chronic liver disease, which can be used as a target for the prevention and treatment of chronic liver disease. Sympathetic ablation is now being used to treat a wide range of diseases, and this has implications for the treatment of chronic liver disease. As an important ablation technology, the nanosecond knife, which relies on nanosecond pulsed electric fields to achieve ablation, has unique advantages and may be a potential treatment option for chronic liver disease. This article reviews the link between sympathetic excitation and chronic liver disease, the progress of ablation of sympathetic nerves for disease treatment, the application of pulsed electric fields in disease treatment, analyzes the feasibility of using pulsed electric fields in the prevention and treatment of chronic liver disease, and looks forward to and summarizes the prospects for the application of pulsed electric fields in the treatment of chronic liver disease and the challenges it faces.

Objective To propose a surgical instrument identification method based on the improved YOLOv8n model, aiming to reduce the errors that are prone to occur in traditional manual counting methods and further protect the safety of patients. Methods Firstly, the SE attention mechanism is introduced in the backbone of the network to enhance the ability of the model to utilize the feature information. Secondly, the model incorporates the BiFPN pyramid structure to more effectively integrate multi-scale features. Finally, WIoU loss function is used to optimize the original network loss function, so as to improve the accuracy of the model. Results The experimental results showed that the performance of the improved YOLOv8n model was significantly better than the original YOLOv8n model in the task of surgical instrument recognition, with mAP50/% and MAP50-95 /% improved by 6.8% and 8%, respectively. Conclusion The improved model is also superior to common algorithms such as YOLOv4 in terms of accuracy, effectively reducing the phenomenon of missing instrument detection, and significantly improving the reliability and accuracy of surgical instrument identification.

Objective In the process of allocating medical resources, traditional triage methods often face problems such as low triage efficiency, inaccurate triage, and privacy leakage. The research aims to establish an intelligent triage model to improve the efficiency, accuracy, and privacy protection capabilities of triage. Methods A triage algorithm was designed by integrating principal component analysis and random forest algorithm, and a dual encryption hospital emergency triage model was constructed by introducing differential privacy and homomorphic encryption techniques. Results The triage algorithm designed in the study achieved convergence after the 4th and 17th iterations on two datasets, with fitting degrees of 96.8% and 98.4%, respectively. It outperformed other algorithms in terms of computational efficiency and triage accuracy. The average computation time of the research model is 0.43s, and the triage accuracy is higher than other triage models within the range of the total privacy protection budget value of (0.01-5). After Affiliated Hospital of Nanjing University of Chinese Medicine applying the emergency triage model in practical applications, the waiting time, triage accuracy, and readmission rate of patients were significantly reduced. The P-values of statistical tests were all less than 0.05, indicating that the model significantly improved the hospital's triage ability. Conclusion The model can efficiently and accurately complete triage while ensuring patient privacy, and improve the utilization of medical resources.

Objective With the implementation of the YY/T 1686-2020 standard and the continuous upgrading of artificial intelligence technologies, certain limitations have emerged in the content of YY/T 1686-2020. Specifically, the terminology within the standard can no longer comprehensively cover or accurately describe the structural components and characteristics of medical electrical equipment or systems utilizing robotic technologies currently available in the market. Consequently, there is a need for further refinement and supplementation of the terminology section. This article introduces the overview of the revised YY/T 1686 and the formulation of key technical indicators, aiming to address the inconsistent descriptions of critical technologies in the market and the misuse of terminology.Methods Through the analysis of key fundamental and technical terminology, a comparison of domestic and international standards, and a survey of existing products in China, we have strengthened our understanding and application of relevant terminology in medical electrical equipment or systems that employ robotic technologies.Results To meet market demands and promote industrial development, the industry standard YY/T 1686-2020 has been revised. The revised standard adds both basic general terminology and technical terminology, and incorporates performance-related terminology based on the functional characteristics of products in the market. In total, the revised standard includes 98 terms, spanning four major categories basic general terminology, technical terminology, structural components, and performance.

Objective To analyze the research status and hot spots in the field of medical consumables management by using knowledge graph, and to reveal the main research direction and trend through multidimensional data statistics. Methods Citespace and Vosviewer software were used to conduct visual analyses on the current state of medical consumables management, including annual publication volume, disciplinary publication volume, keyword clustering, publishing authors, and institutions. Results The selected literatures in the field of medical consumables management were visually analyzed. The analysis of the number of annual publications shows that there is an overall upward trend between 2014 and 2023, but there is a brief decline in the early 2020. Keyword frequency analysis shows that the frequency of words such as fine management, public hospitals, high-value medical consumables and information technology is higher. Keyword frequency analysis shows that medical consumables, fine management, high-value consumables, information and other words have a high frequency. Keyword correlation analysis reveals the importance of terms such as fine management and high-value consumables in optimizing consumables management and improving efficiency. Analysis of publishing authors indicates limited collaboration among researchers but reveals a core cooperation network, while institutional analysis shows a tight collaborative network centered around Shanghai First People's Hospital. Conclusion Based on Citespace and Vosviewer software, the research status in the field of medical consumables management was analyzed， and the research trends and trends in this field were fully revealed, providing profound insight and theoretical support for the development of future research directions.

Objective To improve the efficiency of hospital procurement funds, enhance the economic value, social benefits, and academic influence of large medical equipment configuration, reduce hospital operating costs and patient burden, achieve lean management of medical equipment procurement access, and promote high-quality development of hospitals. Methods Analyze the evaluation ideas and methods of equipment procurement access from four perspectives clinical, medical engineering, finance, and expert. Taking DSA equipment as an example, a three-level evaluation index system for equipment procurement access is constructed based on health economics. At the same time, effective methods and approaches such as on-site investigation, quantitative index grading, matter element model analysis, comprehensive evaluation scoring, and polynomial regression model are adopted to quantitatively and comprehensively analyze the evaluation indicators. Results Based on the construction and analysis of an evaluation system in health economics, this study aims to find a starting point and direction for the admission management of large-scale medical equipment procurement in hospitals, effectively reduce the risk of hospital procurement decisions, and curb the occurrence of misallocation of equipment procurement resources. Conclusion Provide an effective set of evaluation ideas, algorithms, and methods for the procurement and admission of large medical equipment, in order to provide some reference and inspiration for various public hospitals to standardize and do a good job in the procurement and admission management of large medical equipment.

Objective Build and improve the Microbial Laboratory Information Management System (MLIS), solve the problem of manual recording of operation processes by inspectors, and achieve paperless and information-based management of microbial laboratories. Methods Adopting a three-tier C/S architecture, using ORACLE database, NET Framework 4.0 development tool, C # programming language, and referring to CLSI, ISO15189, electronic medical record system application level grading evaluation standards, combined with the actual work needs of microbiological testing personnel, we have developed an MLIS suitable for the microbiological workflow of our hospital. Results MLIS has implemented a mechanism for recording and grading inspection information throughout the entire process of microbial specimen reception, smear preparation, inoculation, cultivation, drug sensitivity testing, and reporting. The average time for specimen reception, registration, and processing has been reduced by 81%. The smear reporting time and positive result reporting time were shortened by 75% and 30% respectively (P<0.01), and the grading reporting rate increased by 100%. Conclusion The clinical microbiological specimen management system has improved the efficiency of laboratory work. The electronic recording of the entire process of microbiological laboratory operations ensures the traceability and reliability of experimental results. The graded reporting mechanism effectively shortens the reporting time, which helps clinical diagnosis and timely targeted treatment, reduces waste of medical resources, and improves the overall level of medical services.

Objective To explore the utilization of process optimization Methods in improving the efficiency of patient care by optimizing the operational process of emergency enhanced CT patients.MethodThe service chain theory was applied to optimize the emergency enhanced CT process in the radiology department of the target hospital. A total of 503 patients who underwent emergency enhanced CT in our hospital were selected as samples and divided into a control group (144 cases, before process optimization) and an observation group (359 cases, after process optimization). The waiting times for examinations in the two groups were compared. Results After controlling for variables such as gender，age and examination site, the waiting time for patients to receive enhanced CT decreased from (1.38±0.93) h before optimization to (0.94±0.42) h after optimization (P=0.001). Patient satisfaction increased from 60.42% to 84.12% (χ2 =32.95, p<0.001).Conclusion The use of the service chain theory can continuously and effectively optimize the patient care process, shorten patient waiting times, and improve the efficiency of medical services. The key to homogenizing medical services across multiple campuses of a hospital lies in establishing a systematic management system.

Objective Tracheal intubation technique is an important means of emergency respiratory management, in order to avoid intubation errors that may cause injury to the patient, the study of electromagnetic localization detection method of tracheal intubation trajectory was carried out, aiming to improve the correctness and efficiency of tracheal intubation, and to cooperate with the study of automated tracheal intubation robot. Methods The correct and incorrect tracheal intubation curves are collected based on the electromagnetic position tracker and the human head and neck model, the curve data are processed and screened using MATLAB, the optimal paths of correct and incorrect tracheal intubation curves are calculated based on the DTW algorithm, and then the similarity between the optimal paths of correct and incorrect tracheal intubation curves and the detected curves are calculated using the DTW algorithm to determine whether this intubation operation is correct or not by comparing the similarity values. The similarity values were compared to determine whether the intubation operation was correct or not. Results The difference between the similarity values of 120 groups of intubation operations and the optimal paths of correct and incorrect is relatively significant, which can be used to determine whether the intubation operation is correct or not. 50 groups of curves were used to test the system, and the correct rate was 100%. Conclusion The tracheal intubation trajectory detection system can detect whether the intubation process is correct or not, assist the doctor's operation, improve the efficiency of intubation and avoid intubation errors and injuries, and is expected to be integrated with the tracheal intubation robot and expand to extend to the detection of gastric tube intubation and other uses, to promote the medical intelligence and telematics.

Objective To construct the clinical specific disease knowledge graph (KG) of stroke based on open medical KG and electronic medical record. Methods Using the Biomedical Informatics Ontology System and structured electronic medical records of stroke patients as knowledge sources, stroke basic glossary, patient feature glossary, stroke concept dictionary, stroke relationship triplet set, and stroke concept terminalogy set were constructed sequentially. The latter two were imported into the Neo4j database to form the stroke-specific disease KG. The KG representation was obtained by KG embedding model and compared among models of TransE, Rotate, and Analogy, etc. with link prediction and triplet classification as evaluation tasks. Additionally, two prediction tasks were designed to predict whether a patient’s hospital stay exceed 7 days or 14 days. Patient vectors were obtained using the skip-gram embedding algorithm, and the performance of these vectors was compared with patient vectors enriched by the knowledge graph in the prediction tasks. Results The established KG of stroke-specific diseases had 215,090 entities and 550,976 relation triplets. The RotatE model could better represent the established KG and showed higher representation performance than other reference models. Patient vectors enriched with the knowledge graph yielded better results in the prediction tasks. Conclusion Using publicly available medical KG combined with patient data, high-quality specialized disease KG can be rapidly constructed, which is expected to support clinical decision making, disease diagnosis, and personalized medicine.

Objective To explore the optimal combination of pre and post weight for applying adaptive statistical iterative reconstruction-V(ASIR-V) in cranial computed tomography(CT) examination. Methods 90 patients with cranial CT plain scanning were divided into group A, group B and group C by applying the random number table method, with 30 cases in each group. 20%, 30% and 40% pre-ASIR-V weight were preset before scanning in group A, group B and group C, respectively; after scanning in each group was completed, image reconstruction was performed with 50%, 60%, 70% and 80% post-ASIR-V weight, and the A5～A8 subgroup,B5～B8 subgroup and C5～C8 subgroup were obtained, respectively. The parameters related to the radiation dose of the three groups of scans, dose length product (DLP), volume CT dose index (CTDIvol), effective dose (ED) and signal to noise ratio (SNR) and contrast to noise ratio (CNR) of the images of each group were recorded respectively; the subjective evaluation of the images was carried out by a double-blind method by two diagnostic imaging physicians applying a 5-point scale. Results In terms of objective evaluation, while the weight of pre-ASIR-V was increasing, the ED was decreasing, and the two showed a linear negative correlation, the ED regression equation was Y=−0.33X+2.71(r2=0.918, P＜0.001);and the SNR value and CNR value among the subgroups of A5～A8, B5～B8, and C5～C8 all increased with the increase of the weight of post-ASIR-V, and the difference was statistically significant (P<0.001). In terms of subjective ratings, the three groups consistently showed a trend of increasing and then decreasing ratings, with subgroups A6, B7, and C7 each obtaining the highest ratings at the same level of pre-ASIR-V weight, while subgroup B7 had the highest subjective rating value of all subgroups. Conclusion At noise index of 3 and tube voltage of 120 KV, the use of 30% pre-ASIR-V weight and 70% post-ASIR-V weight for cranial CT reduces noise, improves image quality, and significantly reduces the radiation dose to the patient.

Objective In response to the need for accurate monitoring of respiratory function, this paper designs a respiratory monitoring device based on the thoracic impedance measurement method. Methods This paper designs a respiratory measurement device using the chest impedance measurement method, and designs its upper computer program. The hardware part makes full use of the digital and analog resources within the CY8C5888 system-on-chip to realize the chest impedance measurement on a single chip, which makes small size and wearable possible, and it combines with the off-chip Bluetooth module to realize wireless data transmission. The upper computer software is developed by LabVIEW, which can accept impedance data, filter the data, analyze the respiratory frequency and monitor the abnormal respiratory frequency; in which the respiratory frequency of the respiratory signal is measured by the dynamic differential threshold method, which can effectively adapt to the signal changes, and improve the accuracy and real-time detection. Results The respiratory monitoring system is small in size and can realize wearable measurement. The upper computer interface can display the respiratory frequency waveform, and after the actual verification of the human body, the average error between the measured respiratory frequency and the actual respiratory frequency is 2.8%, and the error is generally kept within the acceptable range and complies with the requirements of the technical indexes of respiratory rate in the “Multi-Parameter Monitor Calibration Regulations” of JJG 1163-2019, and it is able to real-time measurement and recording of respiratory signals and alarming of abnormal signals. It has been tested in practice and meets the set objectives. Conclusion The device can effectively adapt to signal changes and improve the accuracy and real-time detection. The miniature respiratory monitoring system designed in this paper is expected to be applied in the clinical field and provide more reliable monitoring data for medical personnel.

Objective This study is to explore the preclinical safety of nanosecond pulsed electric field (nsPEF) for breast ablation in goats. Methods The electrode needle connected to the nanosecond pulse tumor ablation system was used to ablate breast tissues. The blood biochemistry, ultrasound image of breast ablation site were detected before operation, after operation and during the follow-up period. Pathological changes of breast tissue were also compared. Results The nsPEF technique was successful in the ablation of breast in goats. No adverse reaction occurred during the operation and no muscle tremors or contractions were observed around the breast during ablation. Ultrasound examination found that the ablation effect was significant during the regular follow-up after the operation. There was no significant difference in blood examination before and after operation. The histopathology showed apoptosis and necrosis in the ablated region, and normal tissue morphology in the non-ablated region. Conclusion Nanosecond pulsed electric field technique is effective and safe in the normal breast tissue.

Objective To establish a clinical application evaluation method for multi center medical imaging equipment by building primary and secondary information platforms. Methods The clinical application data of medical imaging equipment is obtained through a secondary information platform. The raw data is desensitized using methods such as data collection, data governance, and indicator design. Through data space management and data space testing verification techniques, the desensitized data is transmitted to the primary information platform; The first level information platform designs analysis algorithms based on the clinical application evaluation criteria for medical imaging equipment to evaluate the clinical application of the equipment. Results A number of secondary information platforms transmit standardized data lists to the primary information platform through data space management technology, and is able to analyze and evaluate the reliability, availability, functional effect, equipment performance and operating efficiency of medical imaging equipment. Users can intuitively understand the clinical applicability evaluation results of various medical imaging equipment brands through the results displayed on the primary information platform. Taking PET/MR as an example, from the perspective of individual ratings, the reliability evaluation of A brand equipment is 99.69%, and the reliability evaluation of B brand equipment is 98.37%. As of the writing of this article, the reliability of A brand equipment is slightly higher than that of B brand equipment. Taking MRI as an example, the clinical application efficiency among the three brands in August 2024 was 0.61, 0.51, and 0.37, respectively. According to the rank sum test, there was no significant difference in the clinical application efficiency among the three brands of MRI.Conclusion The construction of clinical application evaluation of multi-platform medical imaging equipment can provide systematic technical solutions and platform-wise support for medical institutions to select and verify medical imaging equipment, can provide data support for promoting the quality improvement of domestic-made medical imaging equipment, and can provide research data and basic sharing service platform-wise support for establishing and improving standards and standardized systems on the reliability, clinical application verification and maintenance of our domestic-made medical imaging equipment.