The development measures oxygen concentrations within the body’s tissue to better understand tumors with more aggressive growth patterns.

Diffuse white matter abnormality proved to be a strong predictor of cerebral palsy, Cincinnati Children’s Hospital Medical Center researchers found.

The platform—DystoniaNet—was 98.8% accurate at diagnosing the condition, and with further testing, may soon be in clinics, experts explained recently.

Brown University researchers built their model from scratch and credited a new multiphase approach to its enhanced detection capabilities.

A machine-learning algorithm can predict the onset of osteoarthritis on MRI scans taken years before symptoms begin.

The FDA has granted RadLogics 510(k) clearance for its AI-Powered chest x-ray pneumothorax application.

Not only can different lung diseases look much the same in chest imaging, but distinct diagnoses may present widely dissimilar image patterns in the same patient at the same timepoint, too.

Experts from a pandemic hotspot in Austria reported on the first patients enrolled in an ongoing study, noting significant imaging-based improvements after 12-week follow-up visits.

The researchers said adding MRE to neuroimaging assessments may dramatically help patients understand their specific disease.

In a small group of women with the highest algorithm prediction risk scores, the tool could have spotted 27% of ensuing cancers, experts reported recently.

Experts at Georgia State University are using thousands of datasets and various imaging modalities to investigate bipolar disorder, schizophrenia and depression.

Researchers with Ben-Gurion University of the Negev in Israel presented their work at the 2020 International Conference on Artificial Intelligence in Medicine.