Egnite is highlighting study results of a new artificial intelligence (AI) algorithm for predicting aortic stenosis severity at the Transcatheter Cardiovascular Therapeutics (TCT) 2021 conference held November 4-6 in Orlando, FL.
The company's Disease Progression algorithm was designed to predict the likelihood a patient with moderate aortic stenosis would later be diagnosed with severe stenosis over a one- and two-year period. The software can help physicians identify and prioritize the review of patients with moderate aortic stenosis who are at higher risk of progressing to severe disease, the company said.
Researchers analyzed 719,321 echo exams and found the algorithm was able to successfully predict progression rates for patients with an average error rate of 3.1%.
The algorithm is part of egnite's CardioCare platform, the company's flagship product, which first launched with a suite of predictive algorithms in May 2021.
![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
