Anatomy segmentation and three-dimensional skeletal visualization arrive with this clearance; an injury detection module for clinical decision support is in development on the platform roadmap
An AI model created by researchers at King’s can detect signs of faulty repair mechanisms in ovarian cancer cells, potentially leading to a low-cost, widely accessible diagnostic tool in the future.
As a pathologist, Dr. Christopher Owens has spent his career trying to improve his methods of catching precancerous colorectal polyps in patients. If he could catch cases earlier, fewer people would develop colorectal cancer, he said.
For older adults with heart failure (HF), leaving the hospital alive does not always mean returning to an independent life. Loss of independence can reduce quality of life, increase caregiver burden and raise care needs. Yet most prognostic approaches focus on death or rehospitalization, making it difficult to identify patients likely to survive while losing independence.
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).