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ACR Informatics Fellowship Accepting 2021 Applications

The ACR Informatics Fellowship provides a radiology resident or early-career professional with hands-on experience in the field of informatics, including one-on-one mentoring. The fellow will be introduced to initiatives of the Data Science Institute®, ACR's AI-LAB™, and other ACR Informatics projects as part of a three-part program.

All applications will be reviewed by the Informatics Fellowship Review Committee. Candidates will be notified by email of the decision by early May, and an announcement will be made at the 2021 ACR Annual Meeting. Applicants for the Informatics Fellowship must be eligible for ACR Membership. Information on membership categories and eligibility for membership is available on the ACR website.

Apply today! Applications for the 2021 Informatics Fellowship will be accepted from February 1 - March 31, 2021.

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ACR DSI and Standards Bodies Active in Artificial Intelligence Space

The expansion of artificial intelligence (AI) into the healthcare arena and radiology is accelerating rapidly. Standards bodies such as the Integrating the Healthcare Enterprise (IHE), Digital Imaging and Communications in Medicine (DICOM) and Fast Healthcare Interoperability Resources (HL7/FHIR) continue to actively define the inclusion of new technologies to facilitate the integration of AI into healthcare. The American College of Radiology® (ACR®) continues to be an active participant in the development and maintenance of these standards.
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ACR DSI Working Group Preparing Public Comment on AI Workflow for Imaging

The IHE Radiology Technical Committee has published AI Workflow for Imaging (AIW-I) Rev. 1.0. The document can be downloaded here. Comments submitted by April 29, 2020 will be considered by IHE Radiology. Comments can be submitted here. The AI Workflow for Imaging Profile addresses workflow use cases involving the request, management, and performance of inference tasks on digital image data acquired by an imaging modality.
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JSON Representation of DICOM Structured Reports

DICOM Supplement 219 has begun a 12 month Trial Implementation period before being voted on by the DICOM Standards Committee. This supplement will make report data easier to consume for AI/ML algorithm developers and allow for interactive annotation exchange in a world where AI and PACS will be best of breed and not necessarily all the same vendor.
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ACR DSI Working Group Preparing Public Comment on AI Results

The IHE Radiology Technical Committee has published AI Results (AIR) Rev 1.0 for public comment. The document can be downloaded here . Comments submitted by April 9th, 2020 will be considered by IHE Radiology. Comments can be submitted here . This AI Results Profile addresses the capture, distribution, and display of medical image analysis results. The central use case involves results generated by artificial intelligence (AI) algorithms.
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DSI Announces New FDA-Cleared AI Algorithms

The American College of Radiology® (ACR®) Data Science Institute (DSI) recently released a new list of FDA-cleared artificial intelligence (AI) algorithms related to medical imaging. Each model includes a summary with the model manufacturer, FDA product code, body area, modality, predicate device, product testing and evaluation related to product performance and clinical validation.
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DSI Releases 90 New Radiology AI Use Cases

The American College of Radiology (ACR) Data Science Institute® (DSI) released 90 clinical and non-interpretive use cases for the radiology community in November to more than double the number of freely available use cases on the DSI website to 140.
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American College of Radiology Launches ACR AI-LAB™ to Engage Radiologists in AI Model Development

ACR AI-LAB™ offers radiologists tools designed to help them learn the basics of AI and participate directly in the creation, validation and use of healthcare AI.
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ACR DSI Releases Landmark Artificial Intelligence Use Cases

A first-of-its-kind series of standardized artificial intelligence (AI) use cases from the American College of Radiology Data Science Institute™ (DSI ) will accelerate medical imaging AI adoption.

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ACR DSI Urges AI Standardization, Interoperability and Reportability at NIH Workshop

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Hackathon Testing ACR Platform-Model Communication for AI

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