人工智能用于诊断和基于图像的骨盆器官缩:一个范围审查
Marian Botoncea1,2, Călin Molnar1,2, Vlad Olimpiu Butiurca1,2
1Faculty of Medicine, George Emil Palade University of Medicine, Pharmacy, Sciences and Technology of Targu Mures, 540139 Targu Mures, Romania.
Medicina (Kaunas, Lithuania)
|August 28, 2025
概括
人工智能 (AI) 有望使用医学成像来诊断骨盆器官脱落 (POP). 然而,目前的人工智能应用需要进一步验证和实践测试才能在临床上使用.
科学领域:
- 医学成像
- 人工智能
- 骨盆地疾病
背景情况:
- 骨盆器官脱落 (POP) 是一种普遍的疾病,需要准确的诊断和治疗计划.
- 医学成像在评估POP中起着至关重要的作用.
- 人工智能 (AI),特别是深度学习 (DL),是医学图像分析的快速发展工具.
研究的目的:
- 对基于成像的诊断和POP的解剖评估中AI应用的现有证据进行范围审查.
- 综合用于POP评估的AI方法的发现.
主要方法:
- 根据PubMed,Scopus和Web of Science的PRISMA-ScR指南进行了全面的文献搜索 (2020年1月至2025年4月).
- 包括的研究是那些将AI (CNN,ViT,混合模型) 应用于POP女性的超声波和MRI.
- 八项研究符合纳入标准.
主要成果:
- 人工智能被应用于2D/3D超声波和MRI进行细分,地标定位和脱落分类.
- 卷积神经网络 (CNN) 和视觉转换器 (ViT) 显示出高的诊断准确性.
- 局限性包括依赖内部数据集,有限的解释性以及缺乏外部验证或临床部署.
结论:
- 人工智能有很大的潜力通过医疗图像分析来改善POP诊断.
- 目前的人工智能应用主要是探索性的,需要进一步开发.
- 未来的研究应专注于外部验证,标准化,可解释的人工智能和临床实施,以提高效用.
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