Ishaan Dokania, a sixth-grader from Oregon, is exploring lithium resource identification using satellite imagery and machine ...

For millions of people living with diabetes, the most feared complication is not the disease itself but the quiet, ...

Machine learning predicted activated clotting time during AF ablation, with deep learning achieving 81% accuracy.

A machine-learning model developed by Weill Cornell Medicine investigators may provide clinicians with an early warning of a complication that can occur late in pregnancy. Preeclampsia is a sudden ...

Cost-Effectiveness of Maintaining Higher Stem-Cell Collection Thresholds in the Chimeric Antigen Receptor T-Cell Era for Multiple Myeloma Predicting severe adverse events (SAEs) in oncology is ...

An interpretable machine learning model predicted moderate to severe acute kidney injury risk in ICU patients with acute ...

Two complementary predictors (DAAE-M and ELIE) estimate individualized 5-year progression risk using routine clinical data, extending the prior DAAE framework beyond static baseline risk. Registry ...

Predicting earthquakes has long been an unattainable fantasy. Factors like odd animal behaviors that have historically been thought to forebode earthquakes are not supported by empirical evidence. As ...

Association of the 70-gene assay and homologous recombination deficiency in patients with high risk 2 breast cancers. Model performance by outcome and number of variables. a Concordance index; scores ...

Kerala scientists have developed a dengue early warning system using machine learning, six years of case data and weather ...