Research Progress of Machine Learning in Assistant Detection of Neurodegenerative Diseases
ZHANG Yuanyuan1,2, DU Kejun1,2, QU Zhichuang2, SHU Haifeng1,2, YU Sixun1,2
1. College of Medicine, Southwest Jiaotong University, Chengdu Sichuan 610031, China;
2. Department of Neurosurgery, General Hospital of Western Theater Command, Chengdu Sichuan 610083, China
Abstract：The aging of the population is becoming more and more serious, and the incidence of neurodegenerative diseases is
increasing year by year, which has become an important global medical, public health and social problem. However, the identification,
classification and grading of neurodegenerative diseases are the key to the diagnosis and treatment of neurosurgeons. In recent years,
the rapid development of artificial intelligence and medical imaging technology has provided a good auxiliary role for it, which has
greatly improved the subjectivity of traditional manual film reading. Aiming at the concrete steps of radiomic, the application results
of machine learning and deep learning in two representative neurodegenerative diseases were summarized. The last part summarized
the challenges faced by machine learning and looking forward to the future research direction. It provides a basis for the further
combination of “clinic” and “engineering” in the treatment of auxiliary neurodegenerative diseases.
张元元1,2，杜科均1,2，屈直闯2，树海峰1,2，余思逊1,2. 机器学习在辅助检测神经退行性疾病中的研究进展[J]. 中国医疗设备, 2022, 37(5): 157-160.
ZHANG Yuanyuan1,2, DU Kejun1,2, QU Zhichuang2, SHU Haifeng1,2, YU Sixun1,2. Research Progress of Machine Learning in Assistant Detection of Neurodegenerative Diseases. China Medical Devices, 2022, 37(5): 157-160.
