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心血管医学中的人工智能:临床应用

Thomas F Lüscher^1,2,3,4, Florian A Wenzl^4,5,6,7, Fabrizio D'Ascenzo⁸

¹Royal Brompton and Harefield Hospitals, London, UK.

European heart journal

|August 19, 2024

概括

人工智能和机器学习 (AI/ML) 通过整合大量患者数据来帮助临床医生进行个性化的风险/益处评估. 严格的验证确保AI/ML工具增强临床决策和改善患者护理.

科学领域:

临床医学临床医学
医疗信息学医疗信息学
人工智能的人工智能

背景情况:

临床决策依赖于整合各种患者数据 (人口统计,症状,实验室,成像).
个性化风险效益分析对于最佳的患者管理至关重要.
越来越多的数据量挑战了传统的临床工作流程.

研究的目的:

审查数据革命对临床医学的影响.
突出人工智能和机器学习 (AI/ML) 在现代医疗保健中的作用.
讨论AI/ML在临床实践中的潜在好处和必要的验证.

主要方法:

对临床医学中数据集成和AI/ML当前文献的综述.
分析AI/ML在患者数据准备,特征分析和风险评估中的应用.
讨论算法验证和重新评估的重要性.

主要成果:

AI/ML可以处理和整合大量的患者数据,帮助临床医生.
AI/ML为急性和慢性护理提供了全面的风险评估.
人工智能/ML的整合代表了医学上的重大数据革命.

结论:

通过增强临床任务,AI/ML为医生和患者提供了巨大的好处.
适当的评估和验证对于AI/ML的安全有效的临床使用至关重要.
通过适当的实施,AI/ML已准备好彻底改变临床医学.

关键词:

人工智能的人工智能是人工智能.深度学习是一种深度学习.诊断算法诊断算法这是一个ECGECGECGECGECG.面部识别系统是面部识别系统.图像成像是一种成像.结果预测结果预测.

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