Colonoscopy AI passed meaningful milestones but has miles to go before it sweeps – AI in Healthcare

In one of the studies, the better adenoma detection rate reflected the AIs detection of very small adenomas.

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).

When it came to using AI to help characterize colorectal polyps (CADx), the results were more uniformly favorable toward the emerging technology.

For example, one study saw the addition of CADx as a support tool yield significant improvement in trainee physicians diagnostic accuracy.

A separate study found augmenting physician expertise with CADx lifted endoscopists diagnostic accuracy from 83% to 89%.

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.

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.

The study is posted in full for free.

Previous recent coverage of colonoscopy AI:

AI impressive as a second set of eyes in colonoscopy

FDA approves first-of-its-kind colonoscopy AI

3 reasons humans are irreplaceable by colonoscopy AI

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Colonoscopy AI passed meaningful milestones but has miles to go before it sweeps - AI in Healthcare