A large language model has been developed for use with electronic medical records. The model has shown potential in various applications, including identifying drug safety signals, diagnosing complex medical cases, and assisting with personalized patient education. Research on the model's capabilities and potential clinical uses is ongoing, with studies exploring its effectiveness in areas such as emergency neurological diagnosis and mobility functional status ascertainment.