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Updated: May 13, 2025

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通过自然语言处理算法生成黄斑疾病的诊断报告.

Xufeng Zhao1,2,3, Chunshi Li4, Jingyuan Yang1,2,3

  • 1Department of Ophthalmology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China.

The British journal of ophthalmology
|May 10, 2025
PubMed
概括

自动化自然语言处理 (NLP) 系统在生成黄斑疾病的诊断报告方面表现有前途. 基于规则和深度学习 (DL) 方法都与初级眼科医生进行了评估,AI在特定领域表现相似或优越.

关键词:
诊断测试/调查 诊断测试/调查马库拉 (Macula) 是一个斑点.视网膜 (retina) 是一个视网膜.

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科学领域:

  • 眼科医生 眼科 眼科
  • 人工智能的人工智能
  • 医疗信息学 医疗信息学

背景情况:

  • 准确和及时的诊断报告对于管理黄斑疾病至关重要.
  • 手动报告生成可能耗时,并且受观察者之间的变化影响.

研究的目的:

  • 为了比较基于规则的和深度学习 (DL) 的自然语言处理 (NLP) 系统,用于自动生成黄斑疾病的诊断报告.
  • 评估这些人工智能系统的性能与初级眼科医生相比.

主要方法:

  • 一项涉及1303名患有或没有黄斑疾病的患者2261只眼睛的诊断研究.
  • 分析了眼科图像 (眼底图片,OCT).
  • 基于规则的NLP和基于DL的NLP系统被开发用于生成报告 (损伤描述,诊断,建议).
  • 报告由初级眼科医生评估,并由视网膜专家根据可读性,正确性和建议进行分级.

主要成果:

  • 基于规则的NLP报告在诊断正确性和建议方面表现优于初级眼科医生.
  • 基于DL的NLP报告在病变描述,诊断正确性和建议方面显示得分略低于初级眼科医生 (p<0.05).
  • 与初级眼科医生报告相比,基于DL的NLP报告显示出更高的可读性 (p=0.094).

结论:

  • 一个多式人工智能系统与NLP算法相结合,可以有效地生成四种黄斑疾病的诊断报告.
  • 这些人工智能系统显示出在眼科中作为有价值的工具的潜力,用于生成报告,与初级临床医生相比.