Romiti Silvia, Vinciguerra Mattia, Saade Wael, Anso Cortajarena Iñaki, Greco Ernesto
Department of Clinical Internal Medicine Anaesthesiology and Cardiovascular Sciences, Sapienza University of Rome, Rome, Italy.
MBA IESE, Financial Advisory M&A Transaction Serv. Deloitte, Barcelona, Spain.
Cardiol Res Pract. 2020 Jun 27;2020:4972346. doi: 10.1155/2020/4972346. eCollection 2020.
Cardiovascular disease (CVD), despite the significant advances in the diagnosis and treatments, still represents the leading cause of morbidity and mortality worldwide. In order to improve and optimize CVD outcomes, artificial intelligence techniques have the potential to radically change the way we practice cardiology, especially in imaging, offering us novel tools to interpret data and make clinical decisions. AI techniques such as machine learning and deep learning can also improve medical knowledge due to the increase of the volume and complexity of the data, unlocking clinically relevant information. Likewise, the use of emerging communication and information technologies is becoming pivotal to create a pervasive healthcare service through which elderly and chronic disease patients can receive medical care at their home, reducing hospitalizations and improving quality of life. The aim of this review is to describe the contemporary state of artificial intelligence and digital health applied to cardiovascular medicine as well as to provide physicians with their potential not only in cardiac imaging but most of all in clinical practice.
尽管在心血管疾病(CVD)的诊断和治疗方面取得了重大进展,但它仍然是全球发病和死亡的主要原因。为了改善和优化心血管疾病的治疗效果,人工智能技术有可能从根本上改变我们的心脏病学实践方式,尤其是在成像方面,为我们提供解释数据和做出临床决策的新工具。机器学习和深度学习等人工智能技术还可以通过增加数据的数量和复杂性来提高医学知识,从而挖掘出临床相关信息。同样,新兴通信和信息技术的使用对于创建普及的医疗服务至关重要,通过这种服务,老年人和慢性病患者可以在家中接受医疗护理,减少住院次数并提高生活质量。本综述的目的是描述应用于心血管医学的人工智能和数字健康的当代状况,并向医生介绍其不仅在心脏成像方面,而且最重要的是在临床实践中的潜力。