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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The Seemingly Simple Task of Exploring FDA-Cleared Algorithms for Medical ImagingFebruary 1, 2021 | Sheela AgarwalIf you are thinking about purchasing an AI product, the ACR DSI catalog is a great place to start but you will still have some homework ahead of you.
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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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AI in Brief: Leveraging Latent DataJuly 11, 2022 | Ali Tejani, MD; Po-Hao (Howard) Chen, MD, MBAThis first briefing in our new quarterly series summarizing key research and articles on AI will bring you up to speed on how we are learning from lat...
An Essential Roadmap for AI in RadiologyJuly 7, 2022 | Valeria Makeeva, MDThe 2022 Data Science Summit delved into the complex relationship between AI expectations and strategies for successful AI implementation.
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 ...
Five Ways to Sharpen Your Data Science Skills as a RadiologistMay 10, 2022 | Po-Hao (Howard) Chen, MD, MBAYou don’t need to be a full-time data scientist to keep abreast of the newest technologies.
Overfitting and Generalization of AI in Medical ImagingApril 11, 2022 | Rishi Gadepally, BS, MS2; Paras Lakhani, MDWhen it comes to potential issues with AI models, radiologists must be vigilant.
One AI to Rule Them All: The Need for Multitask AI ToolsMarch 14, 2022 | Nathaniel Linna, MD; Charles E. Kahn, MS, MDMost AI tools focus on a specific problem, slowing AI adoption and frustrating radiologists.
Uniting the Enterprise: Informatics Beyond the Radiology DepartmentFebruary 10, 2022 | Ali Tejani, MDActionable items to create buy-in and effectively lead enterprise-level change.
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?
Major (but Solvable) AI Challenges Get an Assist from ACR ToolsJanuary 11, 2022 | J. Raymond Geis, MDACR has been productive in developing the tools radiologists need to make progress with AI.
Navigating Medical AI Deployment and Continuous EvaluationDecember 17, 2021 | Collin Howser, MD; Brent Savoie, MD, JDWhat lurks in the innovation “valley of death” to prevent your medical AI project from surviving?
Implementing Your AI and Informatics Strategic Road MapSeptember 17, 2021 | Juan C. Batlle, MD, MBAAttending the ACR Imaging Informatics Summit will help you take your organization’s informatics projects from concept to reality.
Key Takeaways from the Data Science SummitAugust 13, 2021 | Po-Hao (Howard) Chen, MD, MBAThe ACR DSI Summit delivered technical, financial, and patient-focused insights into today's imaging AI, providing context on how DSI is facilitating ...
Overcoming Technical Roadblocks to AI Deployment with StandardizationJuly 13, 2021 | Safwan Halabi, MDDICOM Supplement 224 will alleviate the roller-coaster rides of AI deployment by standardizing processing services and applications to help catalyze A...
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.