基于人工智能的自动化国际疾病分类编码:系统审查
Seyyedeh Fatemeh Mousavi Baigi1,2, Masoumeh Sarbaz1, Ali Darroudi1,2
1Department of Health Information Technology, School of Paramedical and Rehabilitation Sciences, Mashhad University of Medical Sciences, Mashhad, Iran.
Journal of medical signals and sensors
|August 27, 2025
概括
人工智能 (AI) 增强了国际疾病分类 (ICD) 的自动化临床编码. 尽管存在数据不平衡等挑战,但人工智能在医疗保健编码中提供了更高的准确性和效率等好处.
科学领域:
- 医疗信息学
- 医疗保健中的人工智能
- 临床编码系统
背景情况:
- 使用人工智能的自动化临床编码对于医疗效率至关重要.
- 国际疾病分类 (ICD) 编码的准确性对于计费和研究至关重要.
- 现有的手动编码过程面临着速度和一致性的挑战.
研究的目的:
- 系统地审查基于人工智能的自动化ICD编码的当前知识.
- 确定和综合这一领域的挑战,好处和未来研究方向.
- 为推进自动化ICD编码系统提供见解.
主要方法:
- 在主要数据库 (PubMed,Embase,Scopus,Web of Science) 进行了系统的文献搜索.
- 遵守系统审查和元分析 (PRISMA) 准则的优先报告项目.
- 包括专注于人工智能驱动的ICD编码挑战,优势和研究缺口的研究;分析了12641份记录中的8份研究.
主要成果:
- 发现了六个主要挑战:标签空间庞大,数据不平衡,文档冗长,可解释性,道德问题以及缺乏透明度.
- 报告强调了10个主要的好处:改善决策,数据标准化和编码精度.
- 提出了八个未来的研究方向:跨学科合作,学习转移,透明度和积极学习.
结论:
- 基于人工智能的自动化ICD编码具有革命性的临床编码潜力.
- 应对已确定的挑战对于成功实施至关重要.
- 建议在转移学习和透明度等领域进行进一步研究,以优化人工智能驱动的编码系统.
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