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

ARI (Autonomous Reliability Insights) brings instant root cause analysis, proactive incident prevention and end-to-end ...

Enterprise software is undergoing a major transformation as machine learning becomes deeply embedded into core digital products. Organizations are no longer using ML only for experimental analytics; ...

New research warns that popular deep learning systems trained for cancer pathology may be relying on hidden shortcuts rather than genuine biological signals.

The development of next-generation metallic materials is entering a transformative era driven by data-driven methodologies. Traditional trial-and-error ...

Researchers developed and validated ElasticNet machine learning models that predict 12-month MMSE and BADL outcomes in ...

This research initiative highlights practical AI and business analytics for decision support across infrastructure, ...

Tiny RNA molecules carried by extracellular vesicles in the bloodstream can accurately predict kidney function decline and cardiovascular risk in chronic kidney disease (CKD), as reported by ...

The other is to invest in high-fidelity digital twins which are deemed to be powerful but costly, data-hungry, and often slow to implement. A practical middle ground is emerging: the disruption-aware ...

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 ...

According to Mercer's 2024 AI in Investment Management global manager survey, 91% of asset managers either currently use AI (54%) or plan to use it within their investment strategy or asset-class ...