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Digital Mammography Meta-Analysis Says AI Performs as Well as Radiologists

Six reader studies on digital mammography revealed a pooled sensitivity rate of 80.8 percent for stand-alone artificial intelligence (AI) in comparison to 72.4 percent for radiologist assessment while seven historic cohort studies showed a 75.8 percent pooled sensitivity rate for stand-alone AI versus 72.6 percent for radiologist interpretation of digital mammography.

In a recent interview, Rajesh Bhayana, M.D., shared insights from new research that compared the abilities of ChatGPT-3.5 and ChatGPT-4 to answer text-based questions akin to those found on a radiology board examination.

In a recent video interview, David Ouyang, M.D., shared insights from two recent studies he co-authored on the use of artificial intelligence (AI) to improve initial assessment of left ventricular ejection fraction (LVEF) on echocardiography and ascertain cardiac risks associated with changes in the left ventricle sphericity index seen on magnetic resonance imaging (MRI).

New Study Shows Viability of Adjunctive AI for Breast Ultrasound

Adjunctive use of an artificial intelligence (AI) software demonstrated nearly equivalent sensitivity and over 28 percent higher accuracy in comparison to radiologist assessment of breast ultrasound images for breast lesions, according to new research presented at the recent Society of Breast Imaging (SBI) conference.

TeraRecon Launches AI-Powered Neuro Suite

The artificial intelligence (AI)-powered Neuro Suite reportedly enables radiologists to access leading neurological AI algorithm solutions in the field, including the brain magnetic resonance imaging (MRI) segmentation capabilities of the Combinostics’ algorithm that can help differentiate degenerative pathologies such as Alzheimer’s disease and dementia.