AI healthcare firm Avenda Health is touting results from a study showing the ability of AI to accurately identify cancer in oncology imaging and diagnostics. The findings were published June 11 in The Journal of Urology.
The study demonstrated that AI-assisted cancer tracking with Unfold AI, Avenda Health’s cancer mapping technology, improved urologists' and radiologists' abilities to identify prostate cancer extent by 45 times.
The readers included in the study initially defined cancer margins manually, and after a period of at least four weeks, used AI software to define cancer margins. Researchers leading the study found that AI-assisted cancer margins significantly outperformed cognitively defined and hemigland margins, with a balanced accuracy of 84.7% compared with 67.2% and 75.9%, respectively.
AI-assisted margins also reduced the underestimation of cancer extent, with a negative margin rate of 72.8% compared with 1.6% for cognitively defined margins. The results show how Unfold AI can improve accuracy in defining prostate cancer margins, leading to improved patient outcomes by informing better treatment strategies, Avenda Health said.
![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)
