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 CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...

A powerful artificial intelligence (AI) tool could give clinicians a head start in identifying life-threatening complications ...

Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Zimmer said SynTuition matched expert’s PJI diagnosis 96% of the time, outperforming pooled physicians who matched experts 91% of the time.

MASLD is prevalent in T2DM patients, with a 65% occurrence rate, and poses a higher risk for severe liver diseases. The study analyzed 3,836 T2DM patients, identifying key predictors like BMI, ...

This model was trained and tested on a 70%/30% split (train/test result cohort), achieving an area under the receiver operator curve on the test set of 0.866 (95% CI, 0.857 to 0.875). Assigning a ...

A particle collision reconstructed using the new CMS machine-learning-based particle-flow (MLPF) algorithm. The HFEM and HFHAD signals come from the ...

Machine learning, a type of artificial intelligence, has many applications in science, from finding gravitational lenses in the distant universe to predicting virus evolution. Hubble Space Telescope ...