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Discretionary Corrigenda (88)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67135, first published .
Correction: Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Correction: Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Correction: Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study

Authors of this article:

Yun Kwan Kim1, 2 Author Orcid Image ;   Won-Doo Seo1 Author Orcid Image ;   Sun Jung Lee1 Author Orcid Image ;   Ja Hyung Koo1 Author Orcid Image ;   Gyung Chul Kim1 Author Orcid Image ;   Hee Seok Song1 Author Orcid Image ;   Minji Lee3 Author Orcid Image
Article Authors Cited by Tweetations Metrics

    Corrigenda and Addenda

    1Technology Development, Seers Technology Co. Ltd., Pyeongtaek-si, Gyeonggi-do, Republic of Korea

    2Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea

    3Department of Biomedical Software Engineering, The Catholic University of Korea, Bucheon-si, Gyeonggi-do, Republic of Korea

    Corresponding Author:

    Minji Lee, PhD

    Department of Biomedical Software Engineering

    The Catholic University of Korea

    43, Jibong-ro

    Bucheon-si, Gyeonggi-do, 14662

    Republic of Korea

    Phone: 82 2 2164 4364

    Email: minjilee@catholic.ac.kr



    In “Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study” (J Med Internet Res 2024;26:e62890) the authors noted one error:

    In "Results", "Subgroup Analysis", Figure 4 has been replaced with Figure 5, as follows:

    ‎
    Figure 4. Model performance in difference patient cohorts from MIMIC-IV and eICU-CRD. (A) AUROC on ICU types of MIMIC-IV. (B) AUROC on ICU types of eICU-CRD. Boxes in the box plot show IQR and the cross marks are outliers with values that lie outside the minimum and maximum ranges of the whiskers, where minimum = Q1 - 1.5 × IQR and maximum = Q3 + 1.5 × IQR. * Statistically significant (P<.05). AUROC: area under the receiver operating characteristic curve; DEWS: Deep Learning–Based Early Warning Score; eICU-CRD: eICU-Collaborative Research Database; ICU: intensive care unit; KNN: k-nearest neighbors; LGBM: light gradient boosting method; LR: logistic regression; MIMIC: Medical Information Mart for Intensive Care; MLP: Multilayer perceptron; NEWS: National Early Warning Score; Q1: first quartile; Q3: third quartile; RETAIN: reverse time attention; SAPS: Simplified Acute Physiology Score.

    In "Results", "External Validation", Figure 5 has been replaced with Figure 4, as follows:

    ‎
    Figure 5. Cross–data set external validation AUROC performance. (A) eICU after training MIMIC-IV. (B) MIMIC-IV after training eICU-CRD. AUROC: area under the receiver operating characteristic curve; DEWS: Deep Learning–Based Early Warning Score; eICU-CRD: eICU-Collaborative Research Database; KNN: k-nearest neighbors; LGBM: light gradient boosting method; LR: logistic regression; MIMIC: Medical Information Mart for Intensive Care; MLP: multilayer perceptron; NEWS: National Early Warning Score; RETAIN: reverse time attention.

    The correction will appear in the online version of the paper on the JMIR Publications website on October 28, 2024 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.

    This is a non–peer-reviewed article. submitted 09.10.24; accepted 09.10.24; published 28.10.24.

    Copyright

    ©Yun Kwan Kim, Won-Doo Seo, Sun Jung Lee, Ja Hyung Koo, Gyung Chul Kim, Hee Seok Song, Minji Lee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 28.10.2024.

    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.