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CORRECTION article

Front. Radiol., 24 November 2025

Sec. Artificial Intelligence in Radiology

Volume 5 - 2025 | https://doi.org/10.3389/fradi.2025.1744006

Correction: Diagnostic precision of a deep learning algorithm for the classification of non-contrast brain CT reports

This article is a correction to:

  1. Diagnostic precision of a deep learning algorithm for the classification of non-contrast brain CT reports

    1. Read original article
Hamza Eren Güzel Hamza Eren Güzel1*Gktu Ac&#x; Göktuğ Aşcı2*Oytun DemirbilekOytun Demirbilek3Tue Doa zdemirTuğçe Doğa Özdemir1Pelin Berfin Erekli Pelin Berfin Erekli1
  • 1Department of Radiology, İzmir City Hospital, İzmir, Türkiye
  • 2School of Science and Technology, IE University, Segovia, Spain
  • 3School of Management, Technical University of Munich, Munich, Germany

A Correction on

Diagnostic precision of a deep learning algorithm for the classification of non-contrast brain CT reports

By Güzel HE, Aşcı G, Demirbilek O, Özdemir TD and Erekli PB (2025). Frontiers in Radiology. 5:1509377. doi: 10.3389/fradi.2025.1509377

In the published article, there was a mistake in the conclusion part of the abstract:

This study revealed decreased diagnostic accuracy of an AI decision support system (DSS) at our institution. Despite extensive evaluation, we were unable to identify the source of this discrepancy, raising concerns about the generalizability of these tools with indeterminate failure modes. These results further highlight the need for standardized study design to allow for rigorous and reproducible site-to-site comparison of emerging deep learning technologies.

This has been corrected to read:

The proposed deep learning algorithm demonstrated high diagnostic accuracy, sensitivity, and specificity in classifying non-contrast brain CT reports. These results indicate the feasibility of automated identification of critical cases, which may support workflow efficiency and timely patient management in radiology practice.

The original version of this article has been updated.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Keywords: artificial intelligence, report classification, computed tomography, deep learning, noncontrast head CT

Citation: Güzel HE, Aşcı G, Demirbilek O, Özdemir TD and Erekli PB (2025) Correction: Diagnostic precision of a deep learning algorithm for the classification of non-contrast brain CT reports. Front. Radiol. 5:1744006. doi: 10.3389/fradi.2025.1744006

Received: 11 November 2025; Accepted: 13 November 2025;
Published: 24 November 2025.

Edited and Reviewed by: Maria Evelina Fantacci, University of Pisa, Italy

Copyright: © 2025 Güzel, Aşcı, Demirbilek, Özdemir and Erekli. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Hamza Eren Güzel, aGFtemFlcmVuZ3V6ZWxAZ21haWwuY29t;Göktuğ AşcıZHJnb2t0dWdhc2NpJiN4MDA0MDtnbWFpbC5jb20=

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.