A. Strangio, I. Leo, J. Sabatino, Margarita Brida, Chiara Siracusa, Nicole Carabetta, P. Zaffino, C. Critelli, Alessandro Laschera, M. Spadea, Daniele Torella, Pierre Sabouret, Salvatore De Rosa
{"title":"Is artificial intelligence the new kid on the block? Sustainable applications in cardiology","authors":"A. Strangio, I. Leo, J. Sabatino, Margarita Brida, Chiara Siracusa, Nicole Carabetta, P. Zaffino, C. Critelli, Alessandro Laschera, M. Spadea, Daniele Torella, Pierre Sabouret, Salvatore De Rosa","doi":"10.20517/2574-1209.2023.123","DOIUrl":null,"url":null,"abstract":"Artificial intelligence (AI) is changing our clinical practice. This is particularly true in cardiology where the clinician is often required to handle a large amount of clinical, biological, and imaging data during decision making. In this context, AI can address the need for fast and accurate tools while reducing the burden on clinicians and improving the efficiency of healthcare systems. With this inevitable shift towards more automated and efficient systems, patients may benefit from a more accurate diagnosis and more tailored treatment. A multitude of clinical applications have already been made available and implemented in several fields of cardiology. The aim of this narrative review is to provide an overall picture of the most recent evidence in the literature about AI implementations, highlighting their potential impact on clinical practice.","PeriodicalId":75299,"journal":{"name":"Vessel plus","volume":"45 1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Vessel plus","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20517/2574-1209.2023.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence (AI) is changing our clinical practice. This is particularly true in cardiology where the clinician is often required to handle a large amount of clinical, biological, and imaging data during decision making. In this context, AI can address the need for fast and accurate tools while reducing the burden on clinicians and improving the efficiency of healthcare systems. With this inevitable shift towards more automated and efficient systems, patients may benefit from a more accurate diagnosis and more tailored treatment. A multitude of clinical applications have already been made available and implemented in several fields of cardiology. The aim of this narrative review is to provide an overall picture of the most recent evidence in the literature about AI implementations, highlighting their potential impact on clinical practice.