| Osteoporosis, a common systemic skeletal disease, is characterized by low bone mass, microstructural damage to bone tissue, and decreased bone strength, leading to increased bone fragility and a higher risk of fractures. However, due to the subtle early symptoms, early diagnosis of osteoporosis is challenging. The "State-Target Theory" provides a new perspective for diagnosing osteoporosis, where the "state" reflects the traditional Chinese medicine (TCM) characteristics of the disease, and identifying the "target" helps guide precise intervention. The combined diagnostic approach of "state-target" demonstrates the strengths of integrating TCM and Western medicine. However, current diagnostic methods are insufficient for comprehensive intervention and management, highlighting the need for artificial intelligence (AI) to assist in the diagnostic process. AI technology plays a significant role in osteoporosis diagnosis, including early screening, medical imaging and clinical data analysis, and predicting the risk of osteoporotic fractures. By combining AI with the "State-Target Theory," we can improve diagnostic accuracy and efficiency, achieve personalized diagnosis and treatment, and also contribute to the objectification of TCM syndromes. |