Researchers have developed a new blood test that could lead to improved brain cancer diagnoses, according to new findings published in Nature Communications.

Machine learning models can tell us a lot about how patients sleep, according to new research published in PLOS One. And it’s much less obtrusive than prior methods.

The British Heart Foundation (BHF) has awarded researchers at University College London (UCL) £1 million ($1.27 million) to study cardiovascular disease. The funding will be used to bring in a new team of researchers and develop a research center focused on AI.

A team of researchers from West Virginia and Arkansas are beginning a four-year project aimed at using AI to improve the treatment of cardiovascular disease and cut healthcare costs.

Insilico Medicine, a Hong Kong-based AI company, has announced a new collaboration with Jiangsu Chia Tai Fenghai Pharmaceutical Co., Ltd. (CTFH) aimed at improving care for breast cancer patients.

Northeastern University in Boston has announced the launch of a new research hub focused on ensuring AI systems help rather than replace humans working in healthcare, cybersecurity and sustainability.

Machine learning can be combined with virtual or augmented reality to train surgery residents in sensitive spinal procedures.

Worldwide, research is booming around AI applications for predicting and treating cancer with ever more precise and personalized approaches. However, a new literature review has found a shortfall of AI-inclusive studies looking at cancer outcomes and survivorship.

Machine learning can read cardiac MRIs with the same accuracy as a physician, with much higher speed, according to a recent study published in Circulation: Cardiovascular Imaging and reported by Cardiovascular Business.

Researchers in Australia are about to begin testing, in humans, a brain-computer interface created to restore communication in people with severe paralysis.  

Auditory specialists placing Cochlear implants in hearing-impaired patients may position the devices better with an assist from AI than with conventional methods. 

There’s plenty of research into the diagnostic accuracy of medical smartphone apps created to supply clinical decision support (CDS). However, few studies have looked at how helpful these apps are in clinical practice.