Machine learning (ML) algorithms could potentially be trained to alter mammography findings, tricking radiologists into make an incorrect diagnosis, according to new research published in the European Journal of Radiology.
Researchers have identified an approach for more accurately diagnosing schizophrenia using AI, bringing some objectivity to the field of neurodevelopmental disorder diagnosis, according to a study published in the May edition of Artificial Intelligence in Medicine.
A combination of the established denoising algorithm NeighShrink and chi-square unbiased risk estimation (CURE) could reduce noise in magnetic resonance (MR) images more effectively than traditional methods, according to research published in Artificial Intelligence in Medicine.
A team at Weill Cornell Medicine has developed an AI algorithm that can identify whether human embryos fertilized in vitro have the potential to progress to successful pregnancies, offering guidance as few as five days after an embryo is implanted.
Pittsburgh-based startup SpIntellx has been awarded a $225,000 research grant by the National Science Foundation to further develop its HistoMapr-Breast system—an AI that images whole-slide samples and acts as a computational guide for pathologists.
Canadian researchers working with Toronto General Hospital-University Health Network have developed a natural language processing (NLP) approach to predicting downstream radiology resource utilization, according to work published in the Journal of the American College of Radiology March 2.