Abstract Radiomics research has been hindered by inconsistent and often poor methodological quality, limiting its potential for clinical translation. To address this challenge, the METhodological Radi...

The use of LLMs in radiology and healthcare as a whole is expanding, making it crucial to start understanding their potential vulnerabilities.

“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and p...

In a new special report, researchers address the cybersecurity challenges of large language models (LLMs) and the importance of implementing security measures to prevent LLMs from being used maliciously in the health care system.

Objectives To investigate the intra- and inter-rater reliability of the total methodological radiomics score (METRICS) and its items through a multi-reader analysis. Materials and methods A total of…

Stay connected with the latest advancements and developments in radiology with ESR Connect - the ultimate streaming platform for imaging professionals. Watch cutting-edge science and advance your…

Objectives To investigate the intra- and inter-rater reliability of the total methodological radiomics score (METRICS) and its items through a multi-reader analysis. Materials and methods A total of 1...

Abstract This statement has been produced within the European Society of Radiology AI Working Group and identifies the key policies of the EU AI Act as they pertain to medical imaging. It offers…

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A podcast devoted to clinical radiology and allied sciences, owned and published by the Radiological Society of North America.

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In a new column, radiologist Paul McCoubrie weighs in on challenges facing radiology today.

Dr. Ali Tejani and Dr. Paul Yi preview RSNA 2024 with Dr. Charles Kahn, Editor-in-Chief of Radiology AI. They discuss key highlights from the past year, including the updated CLAIM guidelines, in...