News | Artificial Intelligence | May 02, 2018

Charles E. Kahn Jr. Named Editor of Radiology: Artificial Intelligence

New journal launching in 2019 will highlight emerging applications of machine learning and artificial intelligence in radiology

Charles E. Kahn Jr. Named Editor of Radiology: Artificial Intelligence

May 2, 2018 – The Board of Directors of the Radiological Society of North America (RSNA) announced that Charles E. Kahn Jr., M.D., M.S., will become editor of the new online journal, Radiology: Artificial Intelligence. The new journal will highlight emerging applications of machine learning and artificial intelligence (AI) in the field of imaging across multiple disciplines. It will provide a way to keep practicing physicians and imaging researchers up to date on the best emerging science in this subspecialty.

Beginning in early 2019, the journal will be published bi-monthly and available exclusively online. RSNA members will receive a complimentary subscription as a member benefit. Original research and editorial submissions to Radiology: Artificial Intelligence will be accepted beginning summer 2018.

Kahn is professor and vice chair of the Department of Radiology at the University of Pennsylvania’s Perelman School of Medicine in Philadelphia since joining the university in 2014. He is also a senior fellow of the Institute for Biomedical Informatics and the Leonard Davis Institute of Health Economics at Penn.

Radiology: Artificial Intelligence is an exciting venture,” Kahn said. “I’m deeply honored for the opportunity to serve as this new journal’s editor, and look forward to working with our authors, reviewers and editorial team to present cutting-edge science in this rapidly growing field.”

A board-certified radiologist with a clinical specialty in abdominal imaging, Kahn’s research interests include health services, comparative effectiveness, decision support, information standards and knowledge representation.

Kahn has served as an associate editor for the journal Radiology, and as an associate editor for the American Journal of Roentgenology (AJR). He has also served as a section editor for the Yearbook of Medical Informatics, a guest editor for the Journal of the American College of Radiology (JACR), and as chair of the Publications Committee of the American Roentgen Ray Society (ARRS).

He has been a reviewer for several scientific journals, including Radiology, RadioGraphics, AJR, Academic Radiology, Journal of the American Medical Informatics Association (JAMIA), Journal of Biomedical Informatics, Journal of Digital Imaging, European Radiology and Artificial Intelligence in Medicine.

Kahn has authored or co-authored more than 110 peer-reviewed articles, and given nearly 100 invited lectures.

“With his extensive editorial experience and profound interest in the fields of artificial intelligence and machine learning, Charles Kahn is a natural fit for this role,” said Mary C. Mahoney, M.D., RSNA board liaison for publications and communications. “The RSNA Board is excited to see where he takes this important new journal.”

For more information: www.rsna.org

 

Related Content

Artificial Intelligence in medical imaging was the top trend and buzz at RSNA 2018.

Artificial intelligence in medical imaging was the major buzz at RSNA 2018. The expo floor had a dedicated area just to highlight artificial intelligence software for medical imaging. More than 150 vendors on the expo floor were showing software using some level of AI or deep learning. 

Feature | Artificial Intelligence | January 17, 2019 | Dave Fornell, Editor
Artificial intelligence (AI) was by far the hottest trend discussed in sessions and across the expo floor at the worl
Artificial Intelligence Advances Threaten Privacy of Health Data
News | Artificial Intelligence | January 04, 2019
Advances in artificial intelligence (AI) have created new threats to the privacy of people's health data, a new...
Videos | Artificial Intelligence | December 12, 2018
This is a quick video tour of the Machine Learning Showcase at the ...
Bay Labs Collaborating With Edwards Lifesciences on AI for Heart Disease Detection
News | Artificial Intelligence | December 10, 2018
Medical artificial intelligence (AI) company Bay Labs announced a collaboration with Edwards Lifesciences focused on...
An example of artificial intelligence-aided clinical decision support software for a heart failure patient from the vendor HealthReveal. The AI pulled in relevant patient data from the electronic medical record and offers recommendations for care based on current American Heart Association (AHA) guidelines. It also offers the citations for where to find the guidelines and prescribing information for the recommended drug. Machine learning for cardiology.

An example of artificial intelligence-aided clinical decision support software for a heart failure patient from the vendor HealthReveal. The AI pulled in relevant patient data from the electronic medical record and offers recommendations for care based on current American Heart Association (AHA) guidelines. It also offers the citations for where to find the guidelines and prescribing information for the recommended drug.

Feature | Artificial Intelligence | December 06, 2018 | Lonny Reisman, M.D.
The consistent provision of guideline-directed medical therapy (GDMT) — care delivered according to established guide
AI Predicts Cardiovascular Disease Risk From CT Scans
News | Artificial Intelligence | November 27, 2018
November 27, 2018 – Zebra Medical Vision and Clalit Health Services announced the completion of a research project th
AI Algorithm Outperforms Most Cardiologists in Heart Murmur Detection
News | Artificial Intelligence | November 11, 2018
At the American Heart Association’s (AHA) Scientific Sessions 2018, Nov. 10-12 in Chicago, Eko presented a clinical...
Overlay Init