Artificial Intelligence-Based Left Ventricular Ejection Fraction by Medical Students for Mortality and Readmission Prediction.
Ziv DadonMoshe Rav AchaAmir OrlevShemy CarassoMichael GliksonShmuel GottliebEvan Avraham AlpertPublished in: Diagnostics (Basel, Switzerland) (2024)
AI-based assessment of reduced systolic function in the hands of medical students, independently predicted 1-year mortality and cardiovascular-related readmission and was associated with unfavorable in-hospital outcomes. AI utilization by novice users may be an important tool for risk stratification for hospitalized patients.
Keyphrases
- artificial intelligence
- medical students
- ejection fraction
- left ventricular
- aortic stenosis
- machine learning
- big data
- deep learning
- cardiovascular events
- heart failure
- blood pressure
- healthcare
- hypertrophic cardiomyopathy
- acute myocardial infarction
- cardiac resynchronization therapy
- mitral valve
- emergency department
- cardiovascular disease
- type diabetes
- adipose tissue
- aortic valve
- adverse drug
- skeletal muscle
- drug induced