{"title":"Revolutionizing Cardiac Care: Artificial Intelligence Applications in Heart Failure Management.","authors":"Areeba Fareed, Rayyan Vaid, Abdulrahmon Moradeyo, Afra Sohail, Ayesha Sarwar, Aashar Khalid","doi":"10.1097/CRD.0000000000000851","DOIUrl":null,"url":null,"abstract":"<p><p>Recent advancements in artificial intelligence (AI) have revolutionized the diagnosis, risk assessment, and treatment of heart failure (HF). AI models have demonstrated superior performance in distinguishing healthy individuals from those at risk of congestive HF by analyzing heart rate variability data. In addition, AI clinical decision support systems exhibit high concordance rates with HF experts, enhancing diagnostic precision. For HF with reduced as well as preserved ejection fraction, AI-powered algorithms help detect subtle irregularities in electrocardiograms and other related predictors. AI also aids in predicting HF risk in diabetic patients, using complex data patterns to enhance understanding and management. Moreover, AI technologies help forecast HF-related hospital admissions, enabling timely interventions to reduce readmission rates and improve patient outcomes. Continued innovation and research are crucial to address challenges related to data privacy and ethical considerations and ensure responsible implementation in healthcare.</p>","PeriodicalId":9549,"journal":{"name":"Cardiology in Review","volume":" ","pages":""},"PeriodicalIF":2.0000,"publicationDate":"2025-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cardiology in Review","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CRD.0000000000000851","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Recent advancements in artificial intelligence (AI) have revolutionized the diagnosis, risk assessment, and treatment of heart failure (HF). AI models have demonstrated superior performance in distinguishing healthy individuals from those at risk of congestive HF by analyzing heart rate variability data. In addition, AI clinical decision support systems exhibit high concordance rates with HF experts, enhancing diagnostic precision. For HF with reduced as well as preserved ejection fraction, AI-powered algorithms help detect subtle irregularities in electrocardiograms and other related predictors. AI also aids in predicting HF risk in diabetic patients, using complex data patterns to enhance understanding and management. Moreover, AI technologies help forecast HF-related hospital admissions, enabling timely interventions to reduce readmission rates and improve patient outcomes. Continued innovation and research are crucial to address challenges related to data privacy and ethical considerations and ensure responsible implementation in healthcare.
期刊介绍：
The mission of Cardiology in Review is to publish reviews on topics of current interest in cardiology that will foster increased understanding of the pathogenesis, diagnosis, clinical course, prevention, and treatment of cardiovascular disorders. Articles of the highest quality are written by authorities in the field and published promptly in a readable format with visual appeal
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