Abstract: With the rapid advancement of technologies such as artificial intelligence, cloud computing, and 5G, the application of digital twin in the field of smart healthcare has become increasingly widespread, leading to the emergence of the concept of medical digital twin. In this domain, patients represent the core and challenge of research on medical digital twins, and the research of medical digital twin on patients can better mining and fulfill patients' healthcare needs, enhancing the quality and efficiency of personalized medical services. Therefore, this paper first conducts a detailed investigation of national policy orientations, academic research trends, and international organizational related to medical digital twin. Secondly, focusing on patient populations, this paper proposed a comprehensive technical framework for medical digital twin, with a detailed analysis of three key technologies: digital support technology, digital twin construction technology, and human-computer interaction technology. Thirdly, this paper discusses the five primary applications of medical digital twin: exercise training, disease prediction, clinical treatment, rehabilitation management, and pharmaceutical testing. Finally, this paper discusses and analyzes the challenges faced by the application of digital twin technology in the field of healthcare, such as data heterogeneity, empiricism, security and privacy, and proposes targeted suggestions.