人工智能在心血管疾病多模式成像中的应用
Marko Milosevic1, Qingchu Jin1, Akarsh Singh2
1Roux Institute, Northeastern University, Portland, ME, United States.
Frontiers in radiology
|January 29, 2024
概括
心血管疾病研究中的人工智能 (AI) 正在通过整合多种数据类型,如医学成像和健康记录来取得进展. 然而,现实世界的临床应用仍然是一个重大挑战.
科学领域:
- 心血管疾病研究研究
- 医学成像分析 医学成像分析
- 人工智能应用程序 人工智能应用程序
背景情况:
- 医疗保健数据是多样化的,包括各种模式.
- 对心血管疾病的传统人工智能通常依赖于单个数据类型.
- 人工智能技术的进步使得多模式数据集成成为可能.
研究的目的:
- 审查最近的AI研究 (过去5年) 在多模式心血管成像.
- 确定整合多种数据源用于心血管分析的进展和挑战.
主要方法:
- 在多模式心血管成像中对人工智能应用进行系统审查.
- 对研究的分析,重点是成像模式的注册,细分和融合.
- 包括MRI,CT,心声回声,X射线和电子健康记录等模式.
主要成果:
- 在MRI和CT扫描的注册,细分和融合方面取得了有希望的结果.
- 关于X射线,心声回声和非成像数据等模式的有限研究.
- 很少有研究使用多模式数据进行心血管预测或分类任务.
结论:
- 对于心血管疾病的多式人工智能仍然存在重大挑战.
- 目前的研究表明潜力,但缺乏现实世界的临床实施和测试.
- 需要进一步发展,以弥合人工智能研究和临床实践之间的差距.
关键词:
这是心脏病,心脏病.心血管疾病的心血管疾病临床成像学 临床成像学融合 融合 融合 融合 融合 融合 融合 融合 融合多模式数据多模式数据注册注册注册注册注册注册注册注册是什么意思细分化 细分化的细分化更多相关视频
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