A Proven Methodology for Building a Strong AI Team


Each week one of our AI team members dedicates a few days to learn novel concepts in deep learning or software engineering and present them to the team – we call these talks “Deep Snips”. We do this mainly by reading academic papers from leading groups, books and blog posts. We are not intimidated by […]

3 Predictions for Radiology AI in 2019

Future of radiology predictions for 2019

2018 was a big year for AI in radiology. The FDA accelerated its clearance process by approving over a dozen medical AI solutions. Tech giants like Philips and GE introduced their own AI technology platforms, promising to address the full process of building, maintaining, deploying and scaling AI solutions. And most importantly, AI is finally […]

We’ve partnered with the ACR Data Science Institute on an Industry-first AI Validation Process

Today is a remarkable day for AI in radiology. I’m honored to announce our partnership with the American College of Radiology Data Science Institute, the University of Rochester Medicine and Nuance Healthcare for an industry-first initiative, contributing to the recently launched ACR-DSI ASSESS-AI registry. Our always-on AI solution is currently deployed at the University of […]

Wider Perspective on the Progress in Object Detection

Object Detection is one of the most mature fields in computer vision. In the last year alone we have seen many novel ideas in object detection that have introduced significant improvements in detection accuracy. I’ve gathered, in my opinion, the 9 most important and useful papers (since October 2016) for a talk I recently presented […]