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相关概念视频

这页已由机器翻译。其他页面可能仍然显示为英文。View in English
  1. 首页
  3. 研究领域
  5. 生物医学和临床科学
  7. 瘤学和致癌症
  9. 预测和预后标志物
  11. 机器学习在结直肠手术后预测术后并发症中的作用的系统审查和元分析:机器学习已经走了多远?

机器学习在结直肠手术后预测术后并发症中的作用的系统审查和元分析:机器学习已经走了多远?

Ali Yasen Mohamedahmed1, Shafquat Zaman2,3, Mosaab Agrof4

  • 1Department of General Surgery, University Hospitals Coventry and Warwickshire NHS Trust, Coventry, UK.

International journal of surgery (London, England)
|August 22, 2025

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在PubMed 上查看摘要

概括
此摘要是机器生成的。

机器学习显示出预测结直肠手术并发症的巨大潜力, 建议进行更多的多中心研究,以证实其广泛的临床有用性.

科学领域:

  • 外科瘤学
  • 医疗信息学
  • 预测分析

背景情况:

  • 结肠直肠手术带有严重的术后并发症风险.
  • 准确预测这些结果对于患者管理和护理优化至关重要.

研究的目的:

  • 系统地评估机器学习 (ML) 在结直肠手术后预测术后结果的临床实用性.
  • 综合ML模型对各种并发症的预测性能的证据.

主要方法:

  • 在主要数据库 (PubMed,MEDLINE,Embase,Google Scholar) 进行了系统的文献搜索.
  • 包括的研究集中在预测结直肠手术后并发症的ML模型上.
  • 曲线下的面积 (AUC) 是主要结果指标,并使用随机效应模型进行聚合分析.

主要成果:

  • 其中包括18项研究,报告了诸如静脉泄漏,死亡率,长时间住院和手术部位感染等并发症.
  • 综合的AUC值显示出强烈的预测性:解漏 (0. 813),死亡率 (0. 867),长时间停留 (0. 810) 和手术部位感染 (0. 802).

结论:

  • 机器学习在预测结直肠手术后并发症方面显示出有前途的临床效用和准确性.
  • 需要进一步精心设计的多中心研究来验证这些ML方法以优化外科护理.
关键词:
大肠直肠手术机器学习术后并发症预测模型

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系统审查和元分析