WPI researchers use machine learning and brain scans to identify age- and sex-specific anatomical patterns that predict ...
COMET, a novel machine learning framework, integrates EHR data and omics analyses using transfer learning, significantly enhancing predictive modeling and uncovering biological insights from small ...
A new machine learning model built using a simple and interpretable approach predicts in-hospital death in patients with ...
Machine learning predicts who will decline faster in Alzheimer’s disease using routine clinic data
Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...
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 ...
More than half of transplant recipients in a large analysis developed chronic graft-versus-host disease, and 15% died from causes other than cancer relapse. Those numbers capture the uneasy truth of ...
Yale researchers have developed a machine learning model, called Immunostruct, that can help scientists create more ...
Using machine learning, an electronic nose can "smell" early signs of ovarian cancer in the blood. The method is precise and, ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results