工作流程
疾病
人工智能
转化式学习
医疗保健
临床实习
临床决策支持系统
重症监护医学
精密医学
医学
计算机科学
机器学习
决策支持系统
数据科学
病理
心理学
物理疗法
经济
数据库
经济增长
教育学
作者
Mohammed Andaleeb Chowdhury,Rodrigue Rizk,J. Christine Chiu,Jing Zhang,Jamie L. Scholl,Taylor J. Bosch,Arun Singh,Lee A. Baugh,Jeff S. McGough,K. C. Santosh,Chien‐Wen Chen
出处
期刊:Biomedicines
[Multidisciplinary Digital Publishing Institute]
日期:2025-02-10
卷期号:13 (2): 427-427
被引量:5
标识
DOI:10.3390/biomedicines13020427
摘要
The application of artificial intelligence (AI) and machine learning (ML) in medicine and healthcare has been extensively explored across various areas. AI and ML can revolutionize cardiovascular disease management by significantly enhancing diagnostic accuracy, disease prediction, workflow optimization, and resource utilization. This review summarizes current advancements in AI and ML concerning cardiovascular disease, including their clinical investigation and use in primary cardiac imaging techniques, common cardiovascular disease categories, clinical research, patient care, and outcome prediction. We analyze and discuss commonly used AI and ML models, algorithms, and methodologies, highlighting their roles in improving clinical outcomes while addressing current limitations and future clinical applications. Furthermore, this review emphasizes the transformative potential of AI and ML in cardiovascular practice by improving clinical decision making, reducing human error, enhancing patient monitoring and support, and creating more efficient healthcare workflows for complex cardiovascular conditions.
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