人工智能支持使用医学成像技术分析关节和关节肌肉:系统性审查
Keke Shi1, Bram Packet2,3, Florian Ramakers2
1Department of Development and Regeneration, Cluster Urogenital Surgery, Biomedical Sciences, KU Leuven, Leuven, Belgium. keke.shi@kuleuven.be.
International urogynecology journal
|October 30, 2025
概括
人工智能 (AI) 在关节 (AS) 和关节肌肉 (LAM) 评估的骨盆底成像中表现有前途. 然而,目前的AI模型需要进一步开发和验证,以便在临床上广泛使用.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 盆地底疾病 盆地底疾病
背景情况:
- 关节 (AS) 和部肌肉 (LAM) 的受伤与盆地疾病有关.
- 医学成像对于评估这些伤害至关重要.
- 人工智能 (AI) 越来越多地应用于盆底成像.
研究的目的:
- 系统地评估关节和关节和肌肉成像中的当前人工智能研究的质量.
- 了解AI在这个领域的好处,局限性和知识差距.
主要方法:
- 在主要数据库 (PubMed,Scopus,Web of Science,Embase,IEEEExplore) 进行了系统的文献搜索.
- 包括专注于AI开发和/或对AS或LAM相关疾病的验证的研究.
- 报告质量使用TRIPOD-AI检查清单进行评估.
主要成果:
- 确定了40项研究,主要使用超声波 (24) 和MRI (16).
- 大多数研究 (27) 涉及骨盆底疾病,细分是最常见的AI任务 (25).
- 人工智能工具在时间效率和临床可接受性方面显示出潜力,尽管报告质量中等 (31项研究满足了50-75%的TRIPOD-AI项目).
结论:
- 人工智能有可能协助盆底成像,特别是在细分任务中.
- 由于数据集多样性,外部验证和报告透明度的局限性,大多数人工智能模型尚未准备好进行广泛的临床采用.
- 未来的研究应该优先考虑改善这些方面,以确保安全和有效的临床转化.
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