AI-LAB Federated Learning to Expand AI Opportunities to More Radiologists
November 16, 2021
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Kendall Schmidt
Radiologists can now get involved and develop expertise by registering their sites to take part in the ACR DSI AI federated learning program on AI-LAB...
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AI Transparency: Why We Should Label Algorithms Like Food ProductsOctober 20, 2021 | Mark Sendak; Christopher Roth; Suresh BaluWhat if radiologists asked algorithm creators “Where can we find the product label and instruction manual, so that what’s inside the packa...
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DSI’s AI Survey Shows ACR Tools in Sync with Member Needs for Deploying AIJune 9, 2021 | Bibb AllenWhile a modest amount of AI is currently in clinical practice, many members plan to purchase AI soon, making ACR’s support valuable for AI integ...
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Are You Sure You Want to Share Your Data to Develop AI?June 14, 2022 | Rebecca Driessen, MD; Nabile Safdar, MD, MPHWhile de-identification of data is notoriously difficult, there are several methods helping radiology applications protect patient privacy and making ...
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Build vs. Buy: The Conundrum of Radiology AIJanuary 13, 2022 | Daniel S. Chow, MD, MBA; Justin Glavis-Bloom, MDHow do you decide whether it’s better to build AI systems internally or to purchase applications from an external vendor?
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AI-LAB Federated Learning to Expand AI Opportunities to More RadiologistsNovember 16, 2021 | Kendall Schmidt, PhDRadiologists can now get involved and develop expertise by registering their sites to take part in the ACR DSI AI federated learning program on AI-LAB...
Drifting Away: When Your A+ Decision-Making AI Machine Falls to Average … or WorseMay 12, 2021 | J. Raymond Geis, MDIt is up to you to be sure your AI model continues to work as expected — and the jury is still out on the best way to do it.
You've Purchased an AI Model. Now What?January 11, 2021 | Walter Wiggins, MD, PhDNow that AI is becoming more accessible, hearing from those who have put a program into place can provide valuable insights.
Democratizing AIDecember 15, 2020 | Dan Cohen-Addad, MDA multi-site federated learning approach to AI algorithm training can protect patient privacy and help make AI development more generalizable to wides...
How ACR Is Making AI Technology Accessible to RadiologistsNovember 17, 2020 | J. Raymond Geis, MDACR is building tools and infrastructure that are secure, user friendly, and radiologist focused.
Addressing Bias in AIAugust 18, 2020 | Monica J. Wood, MDA culture of fairness ensures protection for vulnerable or underrepresented populations.
9 Pillars of Clinical AI: Lessons Learned While Building an AI-Enabled Enterprise Radiology DepartmentJuly 14, 2020 | Panagiotis Korfiatis, PhD; Daniel Blezek, PhD; Sadia Choudhery, MDFollowing these best practices to plan and implement an AI strategy helped Mayo realize AI’s benefits.
How to Make Image-Labeling Projects SuccessfulMarch 21, 2020 | Prasanth Prasanna, MD; Arjun Sharma. MDIn this blog on implementing machine learning projects, we highlight the importance of planning your image-labeling process in advance and discuss con...
My Department's Experience with AIJuly 8, 2019 | Eric Weinberg, MDHow we found an AI technology partner, brought AI to our institution and chose our first project.
Four Barriers to Integrating AI into Radiology PracticeMarch 19, 2019 | Jeff Rudie, MD, PhDThese challenges adversely impact our progress with AI and prevent us from moving forward.