ArticleEuropean heart journal. Digital health2026
Artificial intelligence methods to detect heart failure with preserved ejection fraction within electronic health records: an equitable disease detection model.
Article in European heart journal. Digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Longitudinal phenotyping of heart failure with preserved ejection fraction identifies early- and end-stage disease states.Open heart · 2026Article
- Within a Heartbeat: A Machine Learning Approach Using VCG for Heart Failure Assessment in Sinus Rhythm.Journal of personalized medicine · 2026Article
- Artificial Intelligence for Cardiovascular Care in Action: From Learning to Implementation in Health Systems.JACC. Advances · 2025Review
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Authors and funding
26 authors.
Funding
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Abstract
Aims: Heart failure with preserved ejection fraction (HFpEF) accounts for approximately half of all heart failure cases, with high levels of morbidity and mortality. However, many patients who meet diagnostic criteria for HFpEF do not have a documented diagnosis, particularly in non-White populations where conventional risk scores may underestimate risk. Our aim was to develop and validate a diagnostic prediction model to detect HFpEF based on ESC criteria, AIM-HFpEF. Methods and results: We applied natural language processing (NLP) and machine learning methods to routinely collected electronic health record (EHR) data from a tertiary centre hospital trust in London, UK, to derive the AIM-HFpEF model. We then externally validated the model and performed benchmarking against existing HFpEF prediction models (H2FPEF and HFpEF-ABA) for diagnostic power on the entire external cohort and in patients of non-White ethnicity and patients from areas of increased socioeconomic deprivation. An XGBoost model combining demographic, clinical, and echocardiogram data showed strong diagnostic performance in the derivation dataset [ Conclusion: AIM-HFpEF represents a validated equitable diagnostic model for HFpEF, which can be embedded within an EHR to allow for fully automated HFpEF detection.
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