The challenge of accessing historical patient data for clinical research while maintaining privacy regulations is a significant obstacle in medical science. Synthetic medical records offer a solution to mirror real patient data without compromising privacy. This study evaluates the Llama 2 LLM's capability to create synthetic medical records using zero-shot and few-shot prompting strategies. A novel chain-of-thought approach enhances the model's ability to generate accurate medical narratives without prior fine-tuning, achieving results comparable to fine-tuned models based on Rouge metrics evaluation. The CoT method guides the model through multiple steps of reasoning, improving performance in generating History of Present Illness sections from Chief Complaints.
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by Erlend Frayl... às arxiv.org 03-14-2024
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