人工智能用于基于超声波的妇科瘤诊断:系统性审查
Fatima Siddig Abdalla Mohammed1, Sara Mirghani Ahmed Eisa2, Alsafa Mohamed Abdalla Madani3
1Obstetrics and Gynecology, Najran Armed Forces Hospital, Ministry of Defense Health Services, Najran, SAU.
Cureus
|July 14, 2025
概括
人工智能 (AI) 显著改善了使用超声波的妇科瘤诊断,实现了高精度. 需要进一步的研究来临床整合这些人工智能工具.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 在瘤学瘤学.
背景情况:
- 妇科瘤由于异质性而存在诊断挑战.
- 超声波的解释是主观的,影响诊断的准确性.
- 人工智能用于妇科瘤诊断的临床应用是有限的.
研究的目的:
- 在基于超声波的妇科瘤诊断中系统地审查AI应用.
- 评估人工智能的性能,方法和局限性.
- 引导未来的研究和AI在该领域的临床实施.
主要方法:
- 按照PRISMA 2020指南进行系统审查.
- 在主要的科学数据库 (PubMed,Embase,IEEE Xplore,Scopus,Web of Science) 中进行全面的搜索.
- 包括26项研究,研究通过超声波对妇科瘤诊断的AI模型;使用QUADAS-2评估偏差风险.
主要成果:
- 人工智能模型表现出强大的诊断性能 (准确度75-99.8%,AUC高达0.99).
- 深度学习模型 (CNN,ResNet) 总体上表现优于传统的机器学习.
- 研究中的异质性和有限的前性验证被注意到.
结论:
- 人工智能显示出显著的潜力,可以提高妇科瘤超声波诊断的准确性和可重复性.
- 标准化,外部验证和前性试验对于临床翻译至关重要.
- 未来的研究应该专注于可解释的AI,多样化的数据集和现实世界的临床整合.
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