A new artificial intelligence tool developed by Northwestern Medicine scientists and collaborating institutions can help determine whether genetic variants associated with a severe form of childhood epilepsy will cause disease, according to a study published in the Journal of Clinical Investigation.
An AI system trained on photographs of the face and tongue correctly identified every patient with coronary heart disease (CHD) in a small test, according to a new study from China.
Respiratory disease in children is a major global concern. Clinicians traditionally rely on stethoscopes to detect abnormal lung sounds, but access to auscultation can be limited by the need for in-person visits.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
For several decades, researchers have sought to identify biomarkers capable of accurately predicting the outcome of an infection with a high-risk oncogenic HPV type. Despite significant advances, no viral, immune-related or molecular marker can currently and reliably predict which infections will regress spontaneously and which will progress to more severe disease.
People receiving AI-supported screening for diabetic retinopathy, a leading cause of blindness globally, were almost twice as likely to attend specialist follow-up appointments as those receiving standard screening, according to new research from the London School of Hygiene & Tropical Medicine (LSHTM).
Researchers at The University of Texas MD Anderson Cancer Center and collaborating institutions in Texas developed an artificial intelligence (AI) model that helps explain how immune cells find their way to specific locations in the body and why they avoid others. The findings could help scientists better understand cancer, autoimmune diseases and treatment response.
Nanyang Technological University, Singapore (NTU Singapore) and the Institute of Mental Health (IMH) have developed an artificial intelligence (AI) framework capable of identifying youths at high risk of psychosis from short samples of casual, spontaneous speech.
A patch the size of a Band-Aid, stuck to your forehead, can now do something no traditional sleep study or fitness tracker can: nudge your brain toward a better night’s sleep. William Coon, a sleep scientist at the Johns Hopkins Applied Physics Laboratory, has built a wearable device, meant to be used at home, that listens to brain activity and uses neurostimulation and other techniques to manufacture deep, restorative sleep.
Argus’s Neurora tool is intended to complement clinicians’ professional judgement rather than serve as a standalone diagnostic for autism.