Current status and prospects of digital human GPT in medicine

Research on digital human GPT in medicine mainly focuses on its applications in healthcare. This technology can help doctors make diagnoses faster and more accurately by automatically interpreting medical images and electronic medical records, thereby improving diagnostic accuracy and efficiency. At the same time, it can provide personalized health education and patient care, which can improve the patient experience and increase patient satisfaction and compliance. In addition, GPT can automate the processing of large amounts of textual data, significantly reducing the workload of medical staff and reducing medical costs. Its prediagnosis and health management functions can also help detect and prevent diseases early, reducing the cost of later treatment. When applied in scientific research, GPT can identify anomalies in medical data and help researchers discover new treatments or disease prediction models. It can also automatically generate new hypotheses and protocols based on existing medical knowledge, providing practical recommendations for researchers. In addition, GPT can help solve medical problems and promote the progress of scientific research through reasoning and logical thinking. Looking forward to the future, digital human GPT in medicine has broad development prospects. With the continuous advancement of technology and the increasing demand for medical care, the application of GPT in the medical and health fields will be deeper and more extensive. It can not only improve the quality and efficiency of medical services but also promote innovation in and the development of medical research. At the same time, with the increasing demand for privacy and data security, we must understand how we can ensure the safe storage and processing of sensitive medical data, avoid the risk of data leakage, and maintain patient privacy and data compliance to ensure the future development of digital human GPT in medicine.

Key Words: digital human in medicine; GPT; natural language processing; medical; healthcare