What was once experimental research is now becoming operational backbone across modern energy systems. In the editorial ...

Three faculty members from Johns Hopkins University have been named 2026 Sloan Research Fellows by the Alfred P. Sloan ...

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 ...

The applications and systems that software developers use on a daily basis are evolving as AI quickly becomes integrated into ...

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

PanMETAI combines AI and NMR metabolomics to detect early-stage pancreatic cancer from a blood sample, achieving 93 percent ...

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

Le Ky Nam, the youngest competitor at the 2026 International Artificial Intelligence Olympiad in Slovenia, earned a bronze medal with his practical exam score of 99.26 out of 100.

However, inconsistent travel times and unpredictable congestion continue to undermine service reliability, particularly 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 ...

As social media becomes the core domain of information interaction in the era of big data, the emotional information contained in the vast amount of user-generated content provides an unprecedented ...

A machine learning-driven eNose detects ovarian cancer in blood plasma with 97 % sensitivity and specificity, offering a promising biomarker-agnostic approach.