In one of the studies, the better adenoma detection rate reflected the AIs detection of very small adenomas. <\/p>\n
However, AI CADe was no sharper than the operators eye at detecting polyps of more than 10 mm. In addition, AI CADe flagged more low-risk hyperplastic polyps and did not better at flagging advanced adenomas or sessile serrated lesions (flat polyps with elevated risk of becoming cancerous).<\/p>\n
When it came to using AI to help characterize colorectal polyps (CADx), the results were more uniformly favorable toward the emerging technology. <\/p>\n
For example, one study saw the addition of CADx as a support tool yield significant improvement in trainee physicians diagnostic accuracy.<\/p>\n
A separate study found augmenting physician expertise with CADx lifted endoscopists diagnostic accuracy from 83% to 89%.<\/p>\n
The greatest improvement was noted in novice endoscopists (73.8% to 85.6%), almost reaching the accuracy of experts (89.0%), Parsa and Byrne report. <\/p>\n
These and other demonstrations of AI-aided colonoscopy represent promising steps toward standardization and improvement of colonoscopy quality, and implementation of resect-and-discard and diagnose-and-leave strategies, they comment. Yet issues such as real-world applications and regulatory approval need to be addressed before artificial intelligence models can be successfully implemented in clinical practice.<\/p>\n
The study is posted in full for free.<\/p>\n<\/p>\n
Previous recent coverage of colonoscopy AI:<\/p>\n
AI impressive as a second set of eyes in colonoscopy<\/p>\n
FDA approves first-of-its-kind colonoscopy AI<\/p>\n
3 reasons humans are irreplaceable by colonoscopy AI<\/p>\n
<\/p>\n
Continued here:<\/p>\n
Colonoscopy AI passed meaningful milestones but has miles to go before it sweeps - AI in Healthcare<\/a><\/p>\n","protected":false},"excerpt":{"rendered":" In one of the studies, the better adenoma detection rate reflected the AIs detection of very small adenomas. Continue reading