Constructing an intelligent consultation assistant system based on medical large language models

Background Traditional medical services depend on face-to-face communication and written medical record documentation, which may affects the efficiency of diagnosis and treatment. The development of AI technology, especially the advancement of large language models, provides the possibilities for transformation in the healthcare industry.

Objective To develop an intelligent consultation assistant to improve the quality and efficiency of medical services while offering personalized diagnostic and therapeutic experiences.

Methods Based on the comprehensive large language model, digital Homo sapiens technology and 3D visualization technology, the intelligent inquiry system including patient side, server side and doctor side.

Results The patient side used the virtual doctor image to communicate with the patient in natural language and collected symptoms and medical history; The server side used the language model of the medical field to analyze the data, and gave a preliminary diagnosis combined with the knowledge base; The doctor side displayed the condition through 3D mannequins to assist doctors to quickly understand and formulate treatment plans. The output scheme continuously fine tuned the model through doctors' confirmation and feedback. This system not only improved the efficiency of information collection and processing but also enhanced the speed of diagnosis through 3D visualization technology. Furthermore, the application of large language models allowed for more precise understanding of conditions, supporting personalized medical services.

Conclusion The intelligent consultation assistant not only reduces the workload of doctors, but also provides patients with a more convenient medical experience.