Sunchandandeep Singh Brar, Meenakshi Reddy Yathindra, Juan Sebastian Arias Arango, Erika Aguirre Gutierrez, Fawaz Aldoohan, Princejeet Singh Chahal, Apo Youssef, Mahima Srinidhi Narra, Mahesh Babu Tatineni, Jorge Manuel Aldea Saldaña, Gabriel Ramírez Torres, Pallavi Shekhawat, Vyapti Dave
{"title":"The Narrative Review: Advancements in Heart Failure Diagnosis and Management using Artificial Intelligence: A New Era of Patient Care.","authors":"Sunchandandeep Singh Brar, Meenakshi Reddy Yathindra, Juan Sebastian Arias Arango, Erika Aguirre Gutierrez, Fawaz Aldoohan, Princejeet Singh Chahal, Apo Youssef, Mahima Srinidhi Narra, Mahesh Babu Tatineni, Jorge Manuel Aldea Saldaña, Gabriel Ramírez Torres, Pallavi Shekhawat, Vyapti Dave","doi":"10.2174/011573403X369978250818060357","DOIUrl":null,"url":null,"abstract":"<p><p>Heart Failure (HF) is a prevalent medical illness worldwide that affects millions and is a substantial economic burden. Its epidemiological impact is on the rise due to factors such as the ageing of the population, increasing rates of diabetes and hypertension, and better survival post-myocardial infarction. Some limitations in HF management include diagnostic challenges, sudden progression of the disease, and rising rates of readmission. Continuous monitoring and limited therapeutic interventions add further complexity to care. Artificial Intelligence(AI) is essential in health care and has provided solutions for improving HF management. Techniques like machine learning and deep learning enhance clinical decision-making and patient care. AI helps physicians diagnose HF more precisely through the analysis of imaging and electrocardiograms. Additionally, the patients' risk is calculated using various AI algorithms to develop personalized treatments for each individual. AI will help healthcare providers identify problems early and select appropriate therapies, leading to better outcomes. Further areas for improvement include enhanced data integration, predictive accuracy, patient engagement, data privacy and ethics, as well as integration with clinical workflows. AI technologies will continue to evolve in managing and treating HF; ongoing exploration and development are crucial for its optimization. This review outlines the current progress and potential of AI in the future to ensure better patient care and healthcare practices.</p>","PeriodicalId":10832,"journal":{"name":"Current Cardiology Reviews","volume":" ","pages":""},"PeriodicalIF":2.2000,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Cardiology Reviews","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/011573403X369978250818060357","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Heart Failure (HF) is a prevalent medical illness worldwide that affects millions and is a substantial economic burden. Its epidemiological impact is on the rise due to factors such as the ageing of the population, increasing rates of diabetes and hypertension, and better survival post-myocardial infarction. Some limitations in HF management include diagnostic challenges, sudden progression of the disease, and rising rates of readmission. Continuous monitoring and limited therapeutic interventions add further complexity to care. Artificial Intelligence(AI) is essential in health care and has provided solutions for improving HF management. Techniques like machine learning and deep learning enhance clinical decision-making and patient care. AI helps physicians diagnose HF more precisely through the analysis of imaging and electrocardiograms. Additionally, the patients' risk is calculated using various AI algorithms to develop personalized treatments for each individual. AI will help healthcare providers identify problems early and select appropriate therapies, leading to better outcomes. Further areas for improvement include enhanced data integration, predictive accuracy, patient engagement, data privacy and ethics, as well as integration with clinical workflows. AI technologies will continue to evolve in managing and treating HF; ongoing exploration and development are crucial for its optimization. This review outlines the current progress and potential of AI in the future to ensure better patient care and healthcare practices.
期刊介绍:
Current Cardiology Reviews publishes frontier reviews of high quality on all the latest advances on the practical and clinical approach to the diagnosis and treatment of cardiovascular disease. All relevant areas are covered by the journal including arrhythmia, congestive heart failure, cardiomyopathy, congenital heart disease, drugs, methodology, pacing, and preventive cardiology. The journal is essential reading for all researchers and clinicians in cardiology.