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

What was once experimental research is now becoming operational backbone across modern energy systems. In the editorial ...

Physical artificial intelligence (PAI) is the application of AI and machine learning (ML) algorithms to enable autonomous ...

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; ...

AI in genomics offers transformative opportunities by enhancing drug discovery and personalized medicine through efficient genomic data analysis. Drivers include the surge in genomic data, the focus ...

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

Cybersecurity researchers are warning that the foundations of digital trust are under strain as malware grows more adaptive, evasive and collaborative. In response, a team of Romanian scientists has ...

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 ...

Cognitive Intelligence Platforms (CIPs) represent the convergence of AI, ML, NLP, and advanced analytics into unified enterprise ...

Three faculty members from Johns Hopkins University have been named 2026 Sloan Research Fellows by the Alfred P. Sloan ...