Researchers are using radiomics to narrow patient cohorts down to those who are at the greatest risk of poor lung cancer outcomes.

Experts involved in the study suggest their findings could eventually be used to detect pancreatic cancer in its earliest stages when patients are most likely to respond to interventions favorably.

The model combines clinical data with imaging from head CT scans in individuals with severe traumatic brain injuries to quickly predict 6-month outcomes.

Researchers reported that the artificial intelligence system was able to interpret more than 114,000 screening mammograms using a reading protocol with high sensitivity and specificity.

A model that can achieve accuracy in line with that of radiologists when labeling open-access datasets could be a key factor to overcoming limitations of artificial intelligence implementation, researchers explained in Nature Communications.

Experts involved with the study suggested that these findings could be beneficial in the future of ovarian tumor assessment by providing clinical decision making support.

Homogenous datasets can create unintended research bias that hinders the clinical efficacy of AI applications, experts recently explained in PLOS Digital Health.

A study in Lancet Digital Health reports that a previously validated, high performing AI model committed troublesome errors when confronted with atypical anatomy.