从承诺到实践:对人工智能在腹部放射学中的应用进行范围审查
Anastasia Fotis1, Neeraj Lalwani2,3, Pankaj Gupta4
1Radiology, Albert Einstein College of Medicine, Bronx, USA. anastasia.fotis@einsteinmed.edu.
Abdominal radiology (New York)
|July 28, 2025
概括
人工智能 (AI) 正在彻底改变腹部放射学,在图像分析和工作流效率方面有应用. 临床整合需要进一步的验证和更广泛的模式使用.
科学领域:
- 放射学 放射学是一门学科.
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 越来越多地应用于医学成像.
- 腹部放射学是受益于人工智能进步的关键领域.
研究的目的:
- 综合地绘制AI在腹部放射学中的应用.
- 分析2019-2024年人工智能研究的趋势和发现AI研究的差距.
主要方法:
- 对2019年至2024年间发表的432项研究进行了范围审查.
- 将人工智能应用分类为细分,检测,分类,预测和工作流的优化.
- 分析成像方式 (CT,MRI,超声波,X射线) 和AI模型性能.
主要成果:
- 人工智能在图像细分 (Dice 0.65-0.90) 和分类 (灵敏度 52-100%,特异性 40.7-99%) 中表现出强的表现,特别是在CT扫描上.
- 新兴趋势包括用于病变定位的物体检测和预测模型 (AUC 0.62-0.99),尽管解释性是一个问题.
- 工作流优化研究报告了效率的提高,但缺乏标准化的基准;CT仍然是占主导地位的模式.
结论:
- 人工智能显著影响腹部放射学,在细分和分类方面取得了显著的成功.
- 在现实世界的验证,多模式应用和监管明确性方面仍然存在差距.
- 临床整合需要强有力的验证,实际实施和跨学科的合作.
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