News | Artificial Intelligence | March 05, 2019| Jeff Zagoudis, Associate Editor

New Consensus Document Explores Ethical Use of AI in Radiology

Writing committee accepting comments on 38-page document through April 15

New Consensus Document Explores Ethical Use of AI in Radiology

March 5, 2019 — The American College of Radiology (ACR) is one of seven professional societies behind a new consensus document on the ethics of using artificial intelligence (AI) in radiology. The authors are taking comments on the draft guidance through April 15, 2019, and a finalized document will be produced within the following six months.

The ACR was joined by the following societies in drafting the guidance document:

  • European Society of Radiology (ESR);
  • Radiological Society of North America (RSNA);
  • Society for Imaging Informatics in Medicine (SIIM);
  • European Society of Medical Imaging Informatics (ESMII);
  • Canadian Association of Radiologists (CAR); and
  • American Association of Physicists in Medicine (AAPM)

The document explores ethical considerations for artificial intelligence from several angles, including data use, algorithms and trained models, and actual practice. The writing team reviewed current literature from the fields of computer science and medicine, as well as historical ethical scholarship and material related to the ethics of future scenarios. The document was produced through the combined efforts of philosophers, radiologists, imaging informaticists, medical physicists, patient advocates, and attorneys with experience with radiology in the U.S. the European Union.

“AI has noticeably altered our perception of radiology data — their value, how to use them, and how they may be misused. Rather than simply understanding AI, radiologists have a moral duty both to understand their data, and to use the data they collect to improve the common good, extract more information about patients and their diseases, and improve the practice of radiology,” the statement reads.

The comment period is scheduled to close on April 15, 2019, and a finalized document will be produced within the following six months, according to the draft guidance.

Read the full draft guidance document here.

For more information: www.acr.org

Related Content

An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019.

An example of DiA'a automated ejection fraction AI software on the GE vScan POCUS system at RSNA 2019.

News | Artificial Intelligence | May 26, 2020
May 26, 2020 — DiA Imaging Analysis, a provider of AI based ultrasound analysis solutions, said it received a governm
A list of all the abnormalities the AI model classifies. This illustration only shows three representative leads (DII, V1 and V6).Fig. This is Figure 1 from the Nature Communications article.

A list of all the abnormalities the AI model classifies. This illustration only shows three representative leads (DII, V1 and V6).Fig. This is Figure 1 from the Nature Communications article.

News | Artificial Intelligence | May 19, 2020
May 19, 2020 — Artificial inte...
TeraRecon will accelerate innovation in its advanced visualization and AI platforms for image-related decision support to clinical specialists

TeraRecon's End-to-End AI Ecosystem

News | Artificial Intelligence | March 04, 2020
March 4, 2020 — SymphonyAI Group, an operating group of lea
The FDA granted marketing authorization of the Caption Guidance software to Caption Health Inc. in February 2020. It uses artificial intelligence to guide users to get optimal cardiac ultrasound images in a point of care ultrasound (POCUS) setting.

The Caption Guidance software uses artificial intelligence to guide users to get optimal cardiac ultrasound images in a point of care ultrasound (POCUS) setting.

News | Artificial Intelligence | February 13, 2020
February 13, 2020 — The U.S.

GE Healthcare partnered with the AI developer Dia to provide an artificial intelligence algorithm to auto contour and calculate cardiac ejection fraction (EF). The app is now available on the GE Vscan pocket, point-of-care ultrasound (POCUS) system, as seen here displayed at RSNA 2019. Watch a VIDEO demo from RSNA.

Feature | Artificial Intelligence | February 11, 2020 | Sanjay Parekh, Ph.D. 
February 7, 2020 – At the 2019 Radiological Society...
A new technology for detecting low glucose levels via electrocardiogram (ECG) using a non-invasive wearable sensor, which with the latest artificial intelligence (AI) can detect hypoglycemic events from raw ECG signals has been made by researchers from the University of Warwick.

A new technology for detecting low glucose levels via electrocardiogram (ECG) using a non-invasive wearable sensor, which with the latest artificial intelligence (AI) can detect hypoglycemic events from raw ECG signals has been made by researchers from the University of Warwick.

 

News | Artificial Intelligence | January 13, 2020
A new technology for detecting low glucose levels via electrocardiogram (ECG) using a non-invasive wearable sensor,...
Videos | Artificial Intelligence | November 07, 2019
Piotr Slomka explains how his team at Cedars-Sinai is working on intelligent patient risk prediction algorithms...
AI Could Use EKG Data to Measure Patient's Overall Health Status

Image courtesy of iStock

News | Artificial Intelligence | August 29, 2019
In the near future, doctors may be able to apply artificial intelligence (AI) to electrocardiogram data in order to...
Half of Hospital Decision Makers Plan to Invest in AI by 2021
News | Artificial Intelligence | August 08, 2019
A recent study conducted by Olive AI explores how hospital leaders are responding to the imperative to drive efficiency...