Fareed Areeba, Vaid Rayyan, Moradeyo Abdulrahmon, Sohail Afra, Sarwar Ayesha, Khalid Aashar
From the Department of Medicine, Karachi Medical and Dental College, Karachi, Pakistan.
Department of Medicine and Surgery, Ladoke Akintola University of Technology, Ogbomosho, Nigeria.
Cardiol Rev. 2025 Jan 9. doi: 10.1097/CRD.0000000000000851.
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.
人工智能（AI）的最新进展彻底改变了心力衰竭（HF）的诊断、风险评估和治疗。通过分析心率变异性数据，AI模型在区分健康个体与有充血性心力衰竭风险的个体方面表现出卓越性能。此外，AI临床决策支持系统与HF专家的诊断结果高度一致，提高了诊断精度。对于射血分数降低和保留的HF，AI驱动的算法有助于检测心电图和其他相关预测指标中的细微异常。AI还利用复杂的数据模式帮助预测糖尿病患者的HF风险，以加强对病情的理解和管理。此外，AI技术有助于预测与HF相关的住院情况，从而能够及时进行干预，以降低再入院率并改善患者预后。持续的创新和研究对于应对与数据隐私和伦理考量相关的挑战以及确保在医疗保健中的负责任实施至关重要。
