Empowering Machine Learning in Radiology

Radiology Professionals

Developers & Industry

Patients & Advocates

The American College of Radiology Data Science Institute™ is collaborating with a variety of stakeholders within the radiology field to facilitate the development and implementation of artificial intelligence applications that will help radiology professionals provide improved medical care.

2020 Data Science Summit on Monitoring and Evaluating AI: Challenges and Practical Implications

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ACR AI-LAB™

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 health care AI.

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DSI Use Cases

DSI use cases are scenarios where AI may help improve medical imaging care. They help to ensure that AI tools provide needed information, can be implemented into workflow, and have the potential to improve patient care.

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DSI Services

DSI provides a variety of services to our stakeholders, including:

Expert guidance
AI use cases
Algorithm performance evaluation
Algorithm monitoring
Ancillary services
ACR Assist

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Blog

Making ML Image-Labeling Projects Successful

Plan your machine learning project's image-labeling process in advance and consider the project's priorities before selecting software.

Non-Interpretive AI Offers High-Impact Solutions

It will be years before image-interpretation AI delivers the results we see with non-interpretive AI today.

Buzz that AI Will Replace Radiologists Is Trendy but False Jan 2020

The argument that AI will soon replace radiologists is trendy, but it doesn’t hold up under scrutiny. AI will enhance the value we provide to patients, not replace us.

News

90 New 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.

FDA-Cleared 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.

Ethics of AI Multisociety Statement

This statement highlights that ethical use of AI in radiology should promote well-being, minimize harm, and ensure that the benefits and harms are distributed among stakeholders.