Objective To study and compare the results to prove that it takes a long time to solve the problems of manual bone age interpretation, such as high human subjective influence, poor consistency and stability of results, etc. Methods G-P map, TW score method, Zhonghua 05 and other methods were used to compare bone age X-ray images. Artificial intelligence, artificial interpretation and artificial intelligence-assisted artificial interpretation were studied, and the differences among multiple readers were studied. Results Based on the standard TW3, 250 bone age images of children were compared by artificial intelligence system and doctor, TW3-AI model interpretation efficiency on the average processing time was 1.5±0.2 s, significantly shorter than the doctor’s 525.6±55.5 s. In terms of accuracy and reliability, the root mean square of TW3-AI model and expert interpretation results was 0.50 years, indicating a high degree of consistency between the two. Based on G-P standard, the bone age of 745 patients with abnormal growth and development was estimated. The average time of doctors’ interpretation was about 2 min, and the AI model only needed 1~2 s. In terms of accuracy, the average proportion of the AI system was less than one year from the gold standard, 84.60%. Based on the Chinese 05 standard, the average time of manual group reading was significantly higher than that of AI conformance assisted assessment. Conclusion The intelligent detection system of children’s bone age can complete the imaging analysis of children’s bone age at the second level and provide quantitative results such as ossification center rating and bone age, so as to assist doctors in rapid disease diagnosis and efficacy evaluation, and provide decision-making basis for the diagnosis and treatment of children’s endocrine diseases.