Research on Knowledge Service Model in Medical and Health Field Based on Large Language Model

Medical and health knowledge services play a crucial role in improving the quality of medical services and enhancing public health awareness. With the advent of the artificial intelligence era, the medical and health field is undergoing profound transformations. The challenge of effectively utilizing existing resources to meet the growing demand for high-quality medical and health knowledge has become an urgent issue in this domain. To address this challenge, this study constructs a knowledge service model for the medical and health field based on the large language model. The model consists of four layers: the data layer, knowledge layer, large language model layer, and user layer. The model first integrates multiple types of medical and health data and incorporates medical knowledge and expert experience. It then enhances the adaptability of the large language model in the medical and health field through efficient parameter fine-tuning and retrieval-augmented generation techniques. Finally, the model provides diversified medical and health knowledge services to both the public and professionals. To validate the effectiveness of the proposed knowledge service model, this study conducts case analysis to assess its application in medical health knowledge Q&A and medical image diagnosis. The validation results demonstrate that the knowledge service model constructed in this study effectively leverages the LLM's ability to integrate multimodal medical and health data, meets users' personalized needs, and enables in-depth exploration of medical knowledge and innovation in service model.