利用大型语言模型来生成对患者信息的响应
medRxiv : the preprint server for health sciences
|July 28, 2023
概括
微调的大型语言模型 (LLM) 显示出产生患者门户响应的前景. 克莱尔-朗的模型提供了教育内容,并且在同情和准确性方面与ChatGPT的评分相似.
科学领域:
- 医疗保健中的人工智能
- 自然语言处理用于临床通信.
背景情况:
- 患者门户信息对于患者提供者沟通至关重要.
- 有效和同情的反应对于患者的满意度和护理至关重要.
结论:
- 精心调整的LLM可以通过电子健康记录门户网站显著改善患者与医疗服务提供者的沟通.
- 人工智能产生的反应有可能提高初级保健机构的效率和患者参与度.
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