Objective Geriatric patients often face issues related to polypharmacy and adverse drug events. Re-evaluating prescribed medications and considering deprescribing is critical. Medication discrepancies ...
A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with acute liver failure and reveals top risk drivers.
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...
TEM rolls out new AI tools across oncology, cardiology and mental health, accelerating its push to reshape MedTech innovation ...
Background Despite global efforts to improve nutrition, young women aged 15–24 years in low-income and middle-income countries (LMICs) face persistent dual burdens of malnutrition, marked by high ...
Objective To undertake a contemporary review of the impact of exercise based cardiac rehabilitation (ExCR) for patients with atrial fibrillation (AF). Data sources CENTRAL, MEDLINE, Embase, PsycINFO, ...
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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