Micali Giuseppe, Corallo Francesco, Pagano Maria, Giambò Fabio Mauro, Duca Antonio, D'Aleo Piercataldo, Anselmo Anna, Bramanti Alessia, Garofano Marina, Mazzon Emanuela, Bramanti Placido, Cappadona Irene
IRCCS Centro Neurolesi Bonino-Pulejo, Via Palermo, S.S. 113, C.da Casazza, 98124 Messina, Italy.
Department of Medicine, Surgery and Dentistry, University of Salerno, 84081 Baronissi, Italy.
Healthcare (Basel). 2024 Jul 10;12(14):1380. doi: 10.3390/healthcare12141380.
Cardiovascular and neurological diseases are a major cause of mortality and morbidity worldwide. Such diseases require careful monitoring to effectively manage their progression. Artificial intelligence (AI) offers valuable tools for this purpose through its ability to analyse data and identify predictive patterns. This review evaluated the application of AI in cardiac and neurological diseases for their clinical impact on the general population. We reviewed studies on the application of AI in the neurological and cardiological fields. Our search was performed on the PubMed, Web of Science, Embase and Cochrane library databases. Of the initial 5862 studies, 23 studies met the inclusion criteria. The studies showed that the most commonly used algorithms in these clinical fields are Random Forest and Artificial Neural Network, followed by logistic regression and Support-Vector Machines. In addition, an ECG-AI algorithm based on convolutional neural networks has been developed and has been widely used in several studies for the detection of atrial fibrillation with good accuracy. AI has great potential to support physicians in interpretation, diagnosis, risk assessment and disease management.
心血管疾病和神经系统疾病是全球范围内导致死亡和发病的主要原因。这类疾病需要仔细监测，以有效控制其进展。人工智能（AI）通过分析数据和识别预测模式的能力，为此提供了有价值的工具。本综述评估了AI在心脏和神经系统疾病中的应用及其对普通人群的临床影响。我们回顾了关于AI在神经学和心脏病学领域应用的研究。我们在PubMed、科学网、Embase和Cochrane图书馆数据库中进行了检索。在最初的5862项研究中，有23项研究符合纳入标准。研究表明，这些临床领域最常用的算法是随机森林和人工神经网络，其次是逻辑回归和支持向量机。此外，基于卷积神经网络的心电图AI算法已经开发出来，并在多项研究中广泛用于房颤检测，准确率很高。AI在协助医生进行解读、诊断、风险评估和疾病管理方面具有巨大潜力。
