Key result
Artificial intelligence has the potential to significantly improve heart failure management over the next 20 years through enhanced diagnostics, risk stratification, and novel drug development.
Why the study?
Heart failure is a prevalent disease with substantial morbidity and mortality generating large volumes of digitized data that could be analyzed with artificial intelligence.
Artificial intelligence has emerging applications in heart failure for diagnosis, risk stratification, imaging, and drug development.
Heart Failure is a prevalent disease with significant impacts on morbidity and mortality. Heart failure patients have a large volume of healthcare data which is digitized and can be collated. Artificial intelligence (AI) can then be used to assess the data for underlying patterns. AI systems can be trained to analyze readily available data, such as ECGs and heart sounds, and assess likelihood of heart failure. AI can also risk stratify heart failure patients by analyzing available healthcare data. AI can allow rapid assignment of heart failure patients to specific groups via automated echo analysis, but can also provide information regarding novel imaging bio-markers that may be more useful than left ventricular ejection fraction, such as first phase ejection fraction. AI can be used to assess patients' suitability for existing drugs, whilst also enabling development of novel drugs for known or newly discovered drug targets. Heart Failure as a field, with its multi-modal data set and variability in outcomes, will greatly benefit from the expansion and improvement of AI technology over the next 20 years.
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Bernstein et al. (2025) conducted a review in Heart Failure. Artificial intelligence was evaluated. Artificial intelligence has the potential to significantly improve heart failure management over the next 20 years through enhanced diagnostics, risk stratification, and novel drug development.
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