Development and Validation of Fine-Tuning Techniques for Large Models in Gastric, Cardiovascular and Cerebrovascular Diseases
The goal of this observational study is to leverage the abundant patient resources and standardized medical records from Beijing Friendship Hospital, Xuanwu Hospital, and Beijing Anzhen Hospital, combined with the existing data and knowledge platform of guidelines, consensus, medical literature, and dialogue data from Beijing Haitian Ruisheng Science Technology Co.,Ltd, with Beijing Zhilan Medical Technology Co., Ltd. conducting the fine-tuning, optimization, and validation of the medical large language model. The model is fine-tuned according to the consultation and diagnostic needs of different departments to improve the quality and efficiency of hospital medical services, enhance intelligence, and elevate the level of medical care. Through deployment to hospitals at all levels, it aims to achieve standardized services and support graded diagnosis and treatment. The overall research includes medical big data construction, medical knowledge graph construction, medical large model training and fine-tuning, and large model application platform development and deployment.
• Retrospective Historical Medical Records: patients with stomach, cardiovascular and cerebrovascular diseases from September 2014 to August 2024 were enrolled.
• (1) Age ≥ 18 years; (2) Diagnosed with any of the following: chronic gastritis, gastric cancer, gastro esophageal reflux, coronary artery disease, or stroke.
• Prospective Historical Medical Records: Patients with stomach, cardiovascular and cerebrovascular diseases from September 2024 and August 2027 are enrolled.Outpatient and emergency records are used for large model training, and inpatient records are used for both training and internal validation. Inpatient records are allocated to the training set and internal validation set at a 3:1 ratio. Block randomization is used to reduce bias. Each sample is assigned a raw random number uniformly distributed between 0 and 1. Under the block design, each block contains 4 samples. Within each block, samples are ranked by the raw random number and assigned a random code from 1 to 4. The randomization schedule is prepared by a statistician on a computer system before the start of the study and printed on opaque, sealed envelopes.
⁃ Age ≥ 18 years; (2) Clinically diagnosed with one of the following: chronic gastritis, gastric cancer, gastro esophageal reflux, coronary artery disease, or stroke; (3) Patient or legally authorized representative able to understand the study and provide informed consent; (4) Clinically stable and able to complete the study procedures