To solve a problem, we have to see it clearly. Whether it’s an infection by a novel virus or memory-stealing plaques forming in the brains of Alzheimer’s patients, visualizing disease processes in the body is the first step toward alleviating human suffering. It’s also often the most difficult and costly. But an artificial intelligence (AI) breakthrough by Virginia Tech computer scientists published Sept. 16 in Cell Systems — a high-impact journal dedicated to biological research — is bringing those fog-bound processes into focus.

SAN ANTONIO — September 16, 2025 — Southwest Research Institute (SwRI) and The University of Texas at San Antonio (UT San Antonio) are collaborating to create a detection system to identify pre-ignition in hydrogen internal combustion engines (H₂-ICE). Researchers will combine machine learning (ML) algorithms and artificial intelligence with onboard sensors to help detect pre-ignitions based on their tell-tale signs.

An artificial intelligence (AI) deep learning tool that estimates the malignancy risk of lung nodules achieved high cancer detection rates while significantly reducing false-positive results. 

A research team has unveiled a non-destructive, highly accurate approach for determining the optimal timing of embryo rescue sampling.