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 ...

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

Plants are constantly exposed to a wide array of biotic and abiotic stresses in their natural environments, posing ...

A Hybrid Machine Learning Framework for Early Diabetes Prediction in Sierra Leone Using Feature Selection and Soft-Voting Ensemble ...

A machine learning model predicted cardiac tamponade during AF ablation with high accuracy. Learn how XGBoost may improve ...

Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...

Discover how AI and machine learning are transforming electric utilities—boosting grid reliability, resilience, and ...

The gap between what platforms do and what the law assumes they are is the real Section 230 problem. This isn’t about free speech anymore, but about power and incentives. However well-intentioned or ...

Two educators who use artificial intelligence in their classroom combine prompt engineering, in-class assignments and guardrails.

Explore how core mathematical concepts like linear algebra, probability, and optimization drive AI, revealing its pattern-recognition capabilities.

Thanks to Fink, a software package created by two CNRS engineers, it is now possible to track millions of transient celestial phenomena observed in the sky by the Vera C. Rubin Observatory in Chile, ...