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.
Abstract: Voltage sag, swell, harmonics, and transients are power quality (PQ) disturbances that damage modern electrical apparatus. This paper presents an effective classification approach using ...
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 ...
This project aims to detect and classify 16x16 pixel drawings into 10 categories (Sun, Moon, Tree, etc.) using linear and probabilistic models. The main focus was not just to use high-level libraries, ...
Hybrid Quantum-Classical Algorithm for an Integrated Feature Selection and Logistic Regression Model
Abstract: Feature selection is a pivotal step in machine learning, aimed at reducing feature dimensionality and improving model performance. Conventional feature selection methods, typically framed as ...
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