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 ...
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 ...
Drinking water sources can contain diverse bacterial and viral pathogens, making reliable monitoring essential for public ...
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 ...
A new study shows that machine learning models, particularly Support Vector Machines, predict the shear strength of recycled ...
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 ...
Optimized AI models could help estimate concrete compressive strength in wastewater environments and support future ...
A first-of-its-kind systematic review of 190 studies finds that HASM, Euclidean-enhanced machine learning, and Bayesian ...
22don MSN
What this machine-learning model with 65% accuracy says is coming next for the 10-year Treasury
HSBC says it’s designed a machine-learning model to predict the direction of the most important financial instrument in global markets.
15don MSN
Indian-origin sixth-grader trains machine-learning model to spot lithium deposits with 89% accuracy
Ishaan Dokania, a sixth-grader from Oregon, is exploring lithium resource identification using satellite imagery and machine learning. His project reached 89% accuracy in predicting potential lithium ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results