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ACR Data Science Institute Releases AI Use Cases to Accelerate AI Adoption

By Medimaging International staff writers
Posted on 12 Nov 2018
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Image: The ACR-DSI has released artificial intelligence (AI) use cases that will accelerate medical imaging AI adoption (Photo courtesy of Shutterstock).
Image: The ACR-DSI has released artificial intelligence (AI) use cases that will accelerate medical imaging AI adoption (Photo courtesy of Shutterstock).
The American College of Radiology Data Science Institute (Reston, VA, USA) has released a first-of-its-kind series of standardized artificial intelligence (AI) use cases that will accelerate medical imaging AI adoption. This continually updated, freely available use case series is the product of a previously missing and collaborative framework that enables efficient creation, implementation and ongoing improvement of radiological AI tools.

The ACR-DSI technology oriented use cases in health care-AI (TOUCH-AI) framework leverages multi-specialty, multi-industry expert panels to define clinically relevant use cases for development of medical imaging, interventional radiology and radiation oncology AI algorithms. It establishes a methodology and provides tools and metrics for creating algorithm training, testing and validation of data sets around these use cases. Additionally, it develops standardized pathways for implementing AI algorithms in clinical practice and creates opportunities to monitor their effectiveness through the ACR National Radiology Data Registry, the ACR DSI algorithm monitoring service, Assess-AI and others. It also addresses regulatory, legal and ethical issues regarding medical imaging, interventional radiology and radiation oncology AI.

"The ACR DSI use cases present a pathway to help AI developers solve health care problems in a comprehensive way that turns concepts for AI solutions into safe and effective tools to help radiologists provide better care for our patients," said Bibb Allen Jr., ACR DSI Chief Medical Officer.

"The ACR DSI framework promotes standardization, interoperability, reportability and patient safety in radiological artificial intelligence development that can help usher in a new era of advanced medicine," added Keith J. Dreyer, ACR DSI Chief Science Officer.

Related Links:
American College of Radiology Data Science Institute


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