The study, conducted by researchers at Baylor College of Medicine and Texas Children’s Hospital, appeared in the American Journal of Human Genetics.

A team led by Cedars-Sinai Health Sciences University investigators has created a faster, cheaper way to determine the genes expressed in cancerous tumors. The AI-based tool, which they describe in the journal Cell, could make personalized cancer treatment available to more patients.

Scientists at Houston Methodist have developed an artificial intelligence platform that can decode how cells communicate inside the human body, opening a window into conditions such as Alzheimer’s disease, cancer, and potentially accelerating the search for new treatments.

A routine eye scan might reveal more than whether or not someone needs glasses. It could also help doctors spot signs of osteoporosis years before a broken bone ever happens.

Researchers at Rice University and The University of Texas MD Anderson Cancer Center have developed a compact, artificial intelligence-powered imaging device that could transform how clinicians detect cancer. The technology, which aims to bring high-resolution, real-time diagnostics directly to the point of care, was recently described in a paper published in the Proceedings of the National Academy of Sciences.

Interpreting relatively inexpensive electrocardiograms (ECGs) with an artificial intelligence (AI) algorithm accurately screened patients for a key precursor of heart failure in Kenya.

QIMR Berghofer scientists have developed an AI screening tool that harnesses the power of cutting-edge spatial biology analysis to give pathologists “super vision” to detect hidden genetic markers of cancer in standard patient tissue samples.