Finding such discrepancies is critical to the continuity of patient care, as medical records and reports are often utilized across multiple providers and facilities.
Prior attempts at imaging large fossils such as mammoth tusks failed to capture the full artifact with just one scan, instead requiring multiple partial scans that were subsequently pieced together.
“Although regularly assessing and updating these models is necessary to ensure accurate performance, there is no standard approach to addressing model drift.”
Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains how radiology vendors have developed AI app stores to make it easier to access new FDA cleared AI algorithms.
Keith J. Dreyer, DO, PhD, FACR, American College of Radiology (ACR) Data Science Institute Chief Science Officer, explains 5 developments to watch for in radiology artificial intelligence (AI).
Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans.
"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday.