[人工智能的春天:人工智能与内科病例专家]
A Albaladejo1, A Lorleac'h2, J-S Allain2
1Médecine interne et immunologie clinique, CHU de Rennes, 2, rue Henri-le-Guilloux, 35000 Rennes, France.
像ChatGPT-4和Bard这样的人工智能语言模型在诊断复杂的内科病例方面表现有前途,尽管目前的能力落后于人类专家. 随着人工智能诊断技能快速发展,需要进一步评估.
科学领域:
- 医学教育 医学教育
- 人工智能在医学中的应用
- 临床诊断 临床诊断 临床诊断
背景情况:
- "内部医学之春"是法语内部医师的培训活动,涉及复杂的临床病例.
- 本研究评估了针对这些具有挑战性的病例的非专业化AI语言模型的诊断性能.
研究的目的:
- 评估ChatGPT-4和Bard的诊断能力,使用来自"Printemps de la Médecine Interne"的复杂临床病例.
- 将AI诊断性能与人类内科医生专家的诊断性能进行比较.
主要方法:
- 从2021年和2022年的临床病例"Printemps de la Médecine Interne"被介绍给了ChatGPT-4和Bard.
- 对于不正确的AI诊断,允许第二次尝试.
- 人工智能反应与人类内科医生专家的反应进行了比较.
主要成果:
- 人类专家诊断了12例中的9例;ChatGPT-4诊断了3例,Bard诊断了1例.
- 聊天GPT-4成功诊断出了一个人类专家无法诊断的病例.
- 人工智能模型在几秒钟内提供了答案.
结论:
- 当前人工智能对复杂病例的诊断技能低于人类内科医生,但显示出显著的潜力.
- 人工智能能力的快速发展引发了关于诊断医生的未来角色的问题.
- 未来的"内部医学试点"可能需要调整他们的病例选择,以考虑到人工智能的进步.
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