利用ChatGPT的开放访问版本来增强临床意见
Zachary M Tenner1, Michael C Cottone1, Martin R Chavez1,2
1New York University Grossman Long Island School of Medicine, Mineola, New York, United States of America.
PLOS digital health
|February 5, 2024
概括
像ChatGPT-3.5这样的生成人工智能 (GAI) 工具显示出协助差异诊断的潜力. 然而,目前复杂病例的准确性有限,需要进一步研究以确保安全的临床整合.
科学领域:
- 人工智能在医学中的应用
- 临床决策支持系统 临床决策支持系统
- 医学诊断 医学诊断 医学诊断
背景情况:
- 生成型人工智能 (GAI) 和大型语言模型 (LLM) 正在迅速发展.
- 将GAI整合到临床医学中,带来了新的机遇和挑战.
- 评估用于医疗应用的AI工具对于安全采用至关重要.
研究的目的:
- 评估ChatGPT-3.5在生成复杂差异诊断方面的能力.
- 将人工智能生成的诊断与已建立的医疗病例记录进行比较.
- 在临床场景中了解当前GAI的准确性和局限性.
主要方法:
- 利用了来自新英格兰医学杂志的40个马萨诸塞总医院病例记录.
- 提示聊天GPT-3.5生成差异诊断,然后缩小到最可能的.
- 分析了ChatGPT-3.5的差异列表和最终诊断的准确性.
主要成果:
- 在42.5%的病例中,ChatGPT-3.5将最终诊断包括在最初的差异性清单中.
- 该模型在27.5%的病例中缩小后正确识别了最终诊断.
- 与使用简单首席投诉的研究相比,准确性下降,这表明复杂案件存在挑战.
结论:
- 像ChatGPT这样的GAI工具显示出作为增强的临床意见辅助工具的希望.
- 进一步的研究对于探索复杂的医学诊断中的GAI能力和局限性至关重要.
- 将GAI安全有效地整合到医疗保健中需要持续的调查和监管.
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