MIT researchers have devised a novel method to glean more information from images used to train machine-learning models, including those that can analyze medical scans to help diagnose and treat brain conditions. An active new area in medicine involves training deep-learning models to detect structural patterns in brain scans associated with neurological diseases and disorders, such as Alzheimer's disease and multiple sclerosis.

Wearable fitness trackers have made it all too easy for us to make assumptions about our health. We may look to our heart rate to determine whether we really felt the stress of that presentation at work this morning, or think ourselves healthier based on the number of steps we've taken by the end of the day.

Preliminary findings from two analyses of an ongoing study suggest that cognitive behavioral therapy for insomnia delivered by telemedicine is as effective as face-to-face delivery. Results of a randomized controlled non-inferiority trial show that both delivery methods were equally effective at improving sleep outcomes measured by sleep diaries, reducing self-reported sleep latency and wake after sleep onset while increasing total sleep time and sleep efficiency.

The lives of thousands of people with mobility issues could be transformed thanks to ground-breaking research by scientists at the University of Bristol. The FREEHAB project will develop soft, wearable rehabilitative devices with a view to helping elderly and disabled people walk and move from sitting to a standing position in comfort and safety.

Doctors could soon get some help from an artificial intelligence tool when diagnosing brain aneurysms - bulges in blood vessels in the brain that can leak or burst open, potentially leading to stroke, brain damage or death. The AI tool, developed by researchers at Stanford University and detailed in a paper published June 7 in JAMA Network Open, highlights areas of a brain scan that are likely to contain an aneurysm.

Every parent knows the frustration of responding to a baby's cries, wondering if it is hungry, wet, tired, in need of a hug, or perhaps even in pain. A group of researchers in USA has devised a new artificial intelligence method that can identify and distinguish between normal cry signals and abnormal ones, such as those resulting from an underlying illness.

Many mutations in DNA that contribute to disease are not in actual genes but instead lie in the 99% of the genome once considered "junk." Even though scientists have recently come to understand that these vast stretches of DNA do in fact play critical roles, deciphering these effects on a wide scale has been impossible until now.