Study calls for improvement of commercial AI algorithms

In this study, the researchers aimed to externally validate the technology in a prospective observational study in patients who were scheduled for chest x-rays. They obtained a radiologist’s report for each patient (considered the gold standard) and subsequently compared the findings to the AI algorithm’s findings on the same reports.Image of patient (upper-left) in which, according to the radiologist's report, there is only consolidation, but the algorithm detects an abnormal rib (upper-right), consolidation (lower-left), and two nodules (lower-right). It is worth noting the confusion of a consolidation with mammary tissue and of two nodules with the two mammary areolae. Image courtesy of Scientific Reports. The study was performed with a sample of 278 images and reports, 51.8% of which showed no radiological abnormalities according to the radiologist's report. An analysis revealed that the AI algorithm achieved an average accuracy 95%, a sensitivity of 48%, and a specificity of 98%, according to the researchers. On the plus side, the conditions where the algorithm was most sensitive were in detecting external, upper abdominal, and cardiac and/or valvular implants, the group noted. On the other hand, the conditions where the algorithm was less sensitive were located in the mediastinum, vessels, and bone, they wrote. “The algorithm has been validated in the primary care setting and has proven to be useful when identifying images with or without conditions,” the aut...
Source: AuntMinnie.com Headlines - Category: Radiology Authors: Tags: Digital X-Ray Artificial Intelligence Source Type: news