肺病诊断 (LungDiag):基于电子健康记录进行呼吸系统疾病诊断的人工智能授权,这是一个多中心研究
Hengrui Liang1,2, Tao Yang2,3, Zihao Liu1
1Department of Thoracic Surgery China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease the Key laboratory of Advanced Interdisciplinary Studies Center the First Affiliated Hospital of Guangzhou Medical University Guangzhou China.
人工智能诊断工具LungDiag使用电子健康记录改善了呼吸系统疾病的分类. 它在帮助医生在临床实践中进行更准确,更有效的诊断方面表现有前途.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 肺部病理学 肺部病理学
背景情况:
- 呼吸道疾病是全球重大健康挑战之一.
- 准确和及时的诊断往往受到重叠症状的阻碍,导致错误诊断或治疗延迟.
研究的目的:
- 开发和验证基于人工智能 (AI) 的系统LungDiag,用于准确分类呼吸道疾病.
- 利用自然语言处理 (NLP) 来从电子健康记录 (EHR) 中提取临床特征.
主要方法:
- 利用了31,267名EHR的大队伍进行 LungDiag 系统的培训和内部测试.
- 通过3个外部中心的1142个EHR进行了前性现实世界的验证.
- 采用NLP技术来分析EHR数据以进行疾病分类.
主要成果:
- 在内部测试中,LungDiag实现了高诊断性能,F1得分为0.711的前1个诊断和0.927的前3个诊断.
- 在现实世界的验证中,LungDiag与人类专家和ChatGPT 4.0.0相比显示出更高的性能 (F1评分为0.651对top 1诊断)
- 该系统有效地从EHR中提取疾病分类的关键临床特征.
结论:
- LungDiag显示出作为一种有效工具的巨大潜力,以支持医生更准确,更有效地诊断呼吸系统疾病.
- 人工智能系统在现实环境中的性能表明其临床实用性.
- 建议进一步进行大规模的多中心验证,以确认可概括性和临床影响.
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