Image courtesy by QUE.com The University of North Texas (UNT) is stepping into the future with a new undergraduate major in ...

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 ...

Objectives The optimal maternal age at childbirth has been a topic of bourgeoning literature, with earlier ages offering physiological benefits for maternal recovery. In contrast, later ages to give ...

Overview:Machine learning bootcamps focus on deployment workflows and project-based learning outcomes.IIT and global programs provide flexible formats for appli ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

Data Normalization vs. Standardization is one of the most foundational yet often misunderstood topics in machine learning and ...

BACKGROUND: Mental stress-induced myocardial ischemia is often clinically silent and associated with increased cardiovascular risk, particularly in women. Conventional ECG-based detection is limited, ...

Abstract: sQUlearn introduces a user-friendly, noisy intermediate-scale quantum (NISQ)-ready Python library for quantum machine learning (QML), designed for seamless integration with classical machine ...

A one-day short course presented at the American Meteorological Society (AMS) Annual Meeting 2026 106th AMS Annual Meeting - Houston, TX January 25, 2026 at 8:30 AM - 3:45 PM Central Time (Hybrid) ...

AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...