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.

The promise of artificial intelligence in credit scoring is undeniable. By analyzing vast, non-traditional datasets from ...

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

Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...

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 ...

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

Glucose dysregulation may drive cerebral small vessel disease progression through microstructural brain damage, according to ...

The Challenge of Reintubation in Pediatric Cardiac Surgery Despite impressive advances in pediatric cardiac surgery—with over 91% of patients surviving their procedures—reintubation ...

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 ...

Bangladesh is now the world’s third-largest rice producer, with output rising from 10.9 million metric tons in 1971 to 42.0 million metric tons in 2022. Despite the abundance of the staple crop, ...

Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...

Mastering downtime reduction relies on a resilient, efficient and intelligent operation to optimize equipment life cycles and enhance safety.