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 ...

Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

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

AI & Society, states that algorithmic systems often construct competing but equally valid “model-worlds,” offering empirical support for a philosophical claim that evidence alone cannot uniquely ...

BIOPREVENT’ AI tool predicts transplant-related immune conflict and mortality risk using biomarkers, helping doctors ...

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

Calsoft introduced an AI-powered approach to Test Impact Analysis that eliminates unnecessary test executions in CI/CD ...

Dr. James McCaffrey presents a complete end-to-end demonstration of decision tree regression from scratch using the C# language. The goal of decision tree regression is to predict a single numeric ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...