New study: AI tool detects missed findings with high accuracy

IBM Watson Health Imaging AI whitepaper: AI tool detects missed findings with high accuracy

IBM Watson Health has published a new whitepaper about a recent AI study, available exclusively to AIMed.

Missed findings in radiology are a known problem that can result from a variety of factors such as reader fatigue and clinician distractions. This problem has been exacerbated by an increased study volume and exponentially larger numbers of images produced by multidetector CT scanners, overwhelming radiologists who need to either spend less time per image or work longer hours to get through their required workloads.

Detecting lung nodules is particularly challenging with recent cancer screening programs generating large numbers of studies that burden an already strained system. Failure to diagnose important findings can lead to poor patient outcomes and possible malpractice lawsuits.

The study, by the Imaging team at IBM Watson Health, evaluates an AI tool for automatically identifying CT scans with potential missed pulmonary nodules.

Lead author David Gruen, MD, MBA, FACR, Chief Medical Officer at IBM Watson Health Imaging, will talk more about the study in the “Accelerating adoption” session at AIMed’s Global Summit on Wednesday, May 25.

“With the many demands and pressures placed on Radiology, it is deeply encouraging to see these study results,” said Dr Gruen. “Here is evidence of a technology that can work with clinicians to help imaging organizations raise their confidence and quality in clinical and operational performance.”

IBM Watson Health is a sponsor at AIMed’s Global Summit, taking place live and in person in San Francisco, May 24 to 26, 2022. Book your place now!