在白血病检测和分类中的诊断智能系统:系统性审查和元分析
Mehrad Aria1, Zohreh Javanmard2, Donia Pishdad3
1Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Journal of evidence-based medicine
|February 27, 2025
概括
人工智能 (AI) 和机器学习 (ML) 在从血液涂抹图像中检测和分类白血病方面表现出高准确性. 未来的研究应该专注于外部验证,以使这些AI方法具有更广泛的适用性.
科学领域:
- 血液学 血液学 血液学
- 计算生物学 计算生物学
- 医疗成像医学成像
背景情况:
- 白血病是一种骨髓癌,需要早期诊断才能有效治疗.
- 使用AI和ML进行白血病的自动检测和分类对于及时干预至关重要.
- 周围血液涂抹图像是分析血细胞异常的关键.
研究的目的:
- 对基于人工智能的白血病检测和分类方法的研究进行审查和综合.
- 分析人工智能算法的性能和方法,用于分析白血病诊断的血液涂抹图像.
主要方法:
- 从2015年1月到2023年3月,在四个数据库 (Web of Science,PubMed,Scopus,IEEE Xplore) 进行系统的文献搜索.
- 包括使用ML用于白血病检测和分类的原始期刊文章和会议论文.
- 使用Qiao质量评估工具对包含的研究进行质量评估.
主要成果:
- 在1325个已识别的文章中,有190项研究符合资格.
- 平均ML方法的验证准确率为95.38%.
- 现代的ML技术,特别是深度学习 (DL) 和卷积神经网络 (CNN),主导了这些研究,监督学习是主要范式 (79%).
结论:
- 基于人工智能的算法在检测和分类白血病方面表现出色.
- 这项研究强调了人工智能在提高白血病诊断准确度方面的潜力.
- 未来的研究应该强调外部验证,以确保人工智能模型的普遍性.
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