How people with compromised immune systems respond to vaccines is an important area of immunological research. A study led by ...

A research team funded by the National Institutes of Health (NIH) has developed a versatile machine learning model that could one day greatly expand what medical scans can tell us about disease.

Scientists at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new way to determine atomic structures from nanocrystals previously considered unusable, ...

A study published in The Journal of Engineering Research at Sultan Qaboos University presents an advanced intrusion detection system (IDS) designed to improve the accuracy and efficiency of ...

This research initiative highlights the importance of ethical and explainable artificial intelligence in workforce ...

A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...

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 ...

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

Read more about AI-driven air quality system promises faster, more reliable urban health warnings on Devdiscourse ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 possible variants-more combinations than atoms in the observable universe.

Predicting Parkinson's disease (PD) motor progression remains challenging despite advances in neuroimaging. Blood-based transcriptomic profiling offers a more accessible and cost-effective alternative ...