DeepMind, a London-based AI company acquired by Google back in 2014, is sharing predictions made by its advanced AlphaFold system that could help researchers learn more about the new coronavirus.

Owkin, a New York City-based AI startup, announced it is now working with the University of Pittsburgh to design and validate advanced machine learning models. Once finalized, the new models are expected to have a significant impact in areas such as clinical research and the development of pharmaceuticals.

Countless studies have explored AI’s impact on healthcare providers and the patients they serve—but what about the financial side of things? Looking purely at the bottom line, is AI a wise investment?

AI could provide radiologists with significant value as an advanced peer review tool, according to new findings published in Academic Radiology.

AI technology could play a vital rule in the diagnosis and treatment of aggressive posterior retinopathy of prematurity (AP-ROP) in infants, according to new research published in Ophthalmology.

Proscia, a Philadelphia-based AI technology company, has partnered with the University of California, San Francisco (UCSF) to improve cancer diagnoses and patient outcomes.

A machine learning-powered smartphone application could help patients with a chronic cough document their symptoms over an extended period of time, according to new findings published in Digital Biomarkers.

Researchers have developed a cost-effective technique for breast cancer screening that does not require radiation exposure.

Nocturnal enuresis (NE), or bedwetting, affects up to 20% of 5-year-old children and 5% of 10-year-old children.

An AI-powered wearable sensor can detect changes in heart failure patients before an actual crisis occurs, according to new findings published in Circulation: Heart Failure.

A new international partnership is focused on using AI technology to take a closer look at the human brain and advance amyotrophic lateral sclerosis (ALS) research.  

After poring over the chemical compositions of more than 107 million molecules used to make all sorts of drugs, a machine learning algorithm has plucked out one unexpected candidate that may be medicine’s best hope yet against dreaded superbugs.