Comparative Analysis of Heart Failure with Preserved Vs Reduced Ejection Fraction: Patient Characteristics, Outcomes, Mortality Prediction, and Machine Learning Model Development in the JoHFR.
Mahmoud IzraiqKais AlBalbissiRaed AlawaishehAhmad ToubasiYaman B AhmedMarah MahmoudKaram I KhraimMohammed Al-IthawiObada Mohammad MansourAnoud HamatiFarah A KhraisatHadi Abu-HantashPublished in: International journal of general medicine (2024)
The study underscores the heterogeneity in patient profiles between HFrEF and HFpEF. Integrating machine learning models offers valuable insights into mortality risk prediction in HF patients, highlighting the potential of advanced analytics in improving patient care and outcomes.
Keyphrases
- machine learning
- heart failure
- end stage renal disease
- big data
- case report
- cardiovascular events
- chronic kidney disease
- newly diagnosed
- ejection fraction
- risk factors
- prognostic factors
- type diabetes
- cardiovascular disease
- metabolic syndrome
- atrial fibrillation
- deep learning
- patient reported outcomes
- adipose tissue
- coronary artery disease
- risk assessment
- insulin resistance