使用人工智能自动识别高血压并评估其次要影响:系统审查 (2013-2023)
Anjan Gudigar1, Nahrizul Adib Kadri2, U Raghavendra1
1Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India.
人工智能 (AI) 使用各种数据帮助早期检测高血压 (HTN). 大多数研究使用单一数据类型,但多式联络方法对改善医疗保健系统有希望.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 心血管健康 心血管健康
背景情况:
- 高血压 (HTN) 是一个全球性的健康问题,需要早期检测.
- 人工智能 (AI) 为医学中的自动诊断工具提供了潜力.
- 早期识别高度网和二次高度网对于有效管理至关重要.
研究的目的:
- 系统地审查人工智能技术用于自动高血压 (HTN) 检测.
- 识别用于人工智能模型中用于HTN检测的数据集,技术和分类器.
- 探索多模式数据融合和基于图像的模型用于HTN评估.
主要方法:
- 对人工智能在自动化HTN检测中的应用进行系统的文献审查.
- 分析利用临床数据,生理信号和医学成像的研究.
- 基于数据模式 (单模与多模) 的AI模型的分类.
主要成果:
- 大多数审查的研究采用单一模式方法 (例如,生理信号,医学成像).
- 一小部分研究 (22/122) 使用多模式数据融合.
- 很少有研究整合了临床数据,生理信号和医学成像.
结论:
- 目前用于HTN检测的AI方法主要依赖于单个数据源.
- 多模式数据融合为提高HTN检测精度提供了重大机会.
- 未来的研究应该专注于综合多模式建模,以改善医疗保健系统和早期检测HTN.
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