立场论文:医疗图像分析中的人工智能:进步,临床翻译和新兴的前沿
IEEE journal of biomedical and health informatics
|December 31, 2025
概括
人工智能 (AI) 的进步,包括混合CNN-变压器模型和基础AI,正在增强医学成像分析. 这些创新促进了临床翻译和整合到医疗保健工作流程中,改善了诊断和患者护理.
科学领域:
- 医学成像和人工智能 医学成像和人工智能
- 人工智能技术的临床翻译
- 医疗保健 工作流整合 工作流整合
背景情况:
- 在医学中采用人工智能面临挑战.
- 最近的AI进步为医疗应用提供了解决方案.
- 这篇论文回顾了AI在医学图像和视频分析方面的进展.
研究的目的:
- 审查医疗成像人工智能的最新进展.
- 为医疗保健概述新兴的人工智能范式.
- 突出人工智能的成功临床转化途径.
主要方法:
- 复杂卷积神经网络 (CNN) 变压器架构的审查.
- 应用基础和生成AI模型用于转移学习.
- 实施联合学习以保护隐私的协作.
- 采用可解释和值得信赖的AI方法.
主要成果:
- 最先进的结果在细分,分类,重建,合成和注册.
- 允许对较小的数据集进行转移学习,具有有限的基础真实性.
- 支持维护隐私的多机构合作.
- 通过可解释的人工智能促进临床医生的信任和监管合规性.
结论:
- 人工智能发展正在为整合到放射学,病理学和医疗保健领域铺平道路.
- 混合CNN-变压器模型显示出显著的前景.
- 基础模型和联合学习解决了关键的采用障碍.
- 可解释的人工智能对于道德和可信的部署至关重要.
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