Hello.This is Pharmer.In this article, I will organize how far machine learning can be used for human pharmacokinetics (PK) ...
Machine learning predicted activated clotting time during AF ablation, with deep learning achieving 81% accuracy.
For millions of people living with diabetes, the most feared complication is not the disease itself but the quiet, ...
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 ...
Rice feeds more than half of humanity, yet the world’s paddies face a tightening squeeze: demand is projected to reach 650 ...
2don 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 ...
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 ...
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 ...
A proposed machine learning framework for metabolic dysfunction-associated steatotic liver disease may improve personalized risk prediction.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results