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Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/104952, first published .
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Correction: Confidence Measurement Metrics in Multimodal Large Language Models for Ultrasound-Based Radiology Cases: Comparative Evaluation Study of Self-Reported, Consistency-Based, and Hybrid Methods

Correction: Confidence Measurement Metrics in Multimodal Large Language Models for Ultrasound-Based Radiology Cases: Comparative Evaluation Study of Self-Reported, Consistency-Based, and Hybrid Methods

Authors of this article:

Taewon Han1 Author Orcid Image ;   Jaeseung Shin1 Author Orcid Image ;   Jeong Hyun Lee1 Author Orcid Image ;   Kyowon Gu1 Author Orcid Image

Department of Radiology, Samsung Medical Center, 81 Irwon-ro, Irwon-dong - Gangnam-gu, Seoul, Republic of Korea

Corresponding Author:

Jaeseung Shin, MD, PhD



In “Confidence Measurement Metrics in Multimodal Large Language Models for Ultrasound-Based Radiology Cases: Comparative Evaluation Study of Self-Reported, Consistency-Based, and Hybrid Methods” [1], the authors noted three corrections.

First, the following footnote from Table 2 has been removed:

cStatistically significant results (P<.05) are marked with an asterisk.

Second, the Shannon entropy formula in the Confidence Measurement Metrics section currently appears as:

H=−∑ (i=1 to k) pi log2

The formula now reads:

H=pilog2pi

Last, the cell for “GPT-5” and “Majority vote (5), n (%)” in Table 1 currently reads:

64 (68)

The values in this cell have been replaced with the following:

64 (68.09)

The correction will appear in the online version of the paper on the JMIR Publications website together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article has also been resubmitted to those repositories.

  1. Han T, Shin J, Lee JH, Gu K. Confidence measurement metrics in multimodal large language models for ultrasound-based radiology cases: comparative evaluation study of self-reported, consistency-based, and hybrid methods. J Med Internet Res. Jun 2, 2026;28:e86498. [CrossRef] [Medline]

This is a non–peer-reviewed article. submitted 17.Jun.2026; accepted 17.Jun.2026; published 06.Jul.2026.

Copyright

© Jaeseung Shin, Jeong Hyun Lee, Kyowon Gu. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 6.Jul.2026.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.