Avenda Health's Unfold AI Outperforms MRI in Prostate Cancer Prediction
Avenda Health has announced new study results showing that its AI-driven cancer mapping tool, Unfold AI, significantly outperforms MRI in predicting the spread of prostate cancer. In a press release, the company detailed findings presented at the American Urological Association's 2025 Annual Meeting, where Unfold AI achieved a 92% accuracy rate in predicting seminal vesicle invasion (SVI), compared to 52% with standard MRI interpretation.
The study involved two cohorts of men who underwent MRI scans before prostate cancer surgery. Researchers from Stanford University School of Medicine and UCLA's David Geffen School of Medicine compared the accuracy of SVI predictions made by Unfold AI against those made by physicians using MRI alone. The results showed that Unfold AI not only identified more cases accurately but also reduced false positive rates significantly.
These findings build on previous research that highlighted Unfold AI's ability to predict extracapsular extension risk, further establishing its role in enhancing prostate cancer diagnosis and treatment planning. The project received partial funding from the National Cancer Institute at the National Institutes of Health.
We hope you enjoyed this article
Consider subscribing to one of our newsletters like Life AI Weekly or Daily AI Brief.
Also, consider following us on social media:
More from Life Sciences
Oct 17 Masimo Gets FDA Clearance for AFib Detection on Radius VSM Oct 16 Study Tests Smartphone AI for Children's Lung Sounds Oct 16 Manhattan Physician Invests in RunPractice Oct 16 Attilio appoints Buck Institute CEO Eric Verdin as cochairman Oct 16 Aignostics launches HETA Clinical for pathology workflowsLife AI Weekly
Weekly coverage of AI applications in healthcare, drug development, biotechnology research, and genomics breakthroughs.
Whitepaper
Tensordyne Napier: What If One Rack Could Do the Work of Nine?
Tensordyne
This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.
Read moreYou may also like
NYU Langone Tests AI Tool to Fill Radiology Training Gaps
Medical Image Analysis Software Market Forecast to Reach $6.3 Billion by 2031
LUNGevity Awards $2 Million for Lung Nodule Risk Studies
AIRS Medical Gets FDA Clearance for MRI Body Composition Tool
SimBioSys Gets FDA Clearance for AI Breast Cancer Recurrence Tool
Daily AI Brief: the AI news that matters, in your inbox.