Large language models with supervised fine-tuning for inflammatory bowel disease diagnosis and prognosis

Figure 1  The final training loss curve.

Figure 2 The process of constructing the medical corpus and training the model. EHR: Electronic health record; D-P: Doctor-patient; SFT: Supervised fine-tuning; IBD: Inflammatory bowel disease.

Figure 3  Testing and scoring process of the general large language model.

Figure 4 The assessment results of the Doubao. A: The ability in medical history collection and disease diagnosis; B: The ability in output stability; C: The ability of the appropriateness of the output content.

Figure 5 Head-to-head comparison between resident physicians and the inflammatory bowel disease-large language model. LLM: Large language model; SFT: Supervised fine-tuning; IBD: Inflammatory bowel disease.

Figure 6 Evaluated and averaged across three consultant-level gastroenterologists. A: Rating in five domains; B: Total scores (defined as the sum of domain-specific scores); C: Evaluated and averaged across three consultant-level gastroenterologists. LLM: Large language model; SFT: Supervised fine-tuning.

Figure 7 Clinical scenarios with and without inflammatory bowel disease-large language model assistance. LLM: Large language model; AI: Artificial intelligence; IBD: Inflammatory bowel disease.