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Discretionary Corrigenda (59)

Published on in Vol 14 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/78287, first published .
Correction: Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study

Correction: Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study

Correction: Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study

Authors of this article:

Ramon E Diaz-Ramos1 Author Orcid Image ;   Isabella Noriega2 Author Orcid Image ;   Luis A Trejo3 Author Orcid Image ;   Eleni Stroulia1 Author Orcid Image ;   Bo Cao4 Author Orcid Image
Article Authors Cited by Tweetations Metrics

    Corrigenda and Addenda

    1Department of Computing Science, University of Alberta, Edmonton, AB, Canada

    2School of Engineering and Sciences, Tecnologico de Monterrey, Monterrey, Mexico

    3School of Engineering and Sciences, Tecnologico de Monterrey, Atizapan, Mexico

    4Department of Psychiatry, University of Alberta, Edmonton, AB, Canada

    *all authors contributed equally

    Corresponding Author:

    Ramon E Diaz-Ramos, MS

    Department of Computing Science

    University of Alberta

    8900 114 St NW

    Edmonton, AB, T6G 2S4

    Canada

    Phone: 1 780 492 2285

    Email: diazramo@ualberta.ca



    In "Using Wearable Devices and Speech Data for Personalized Machine Learning in Early Detection of Mental Disorders: Protocol for a Participatory Research Study" (JMIR Res Protoc 2023;12:e48210), the authors noted an error.

    The following references:

    32. Chen I-M, Lin P-H, Wu V-C, Wu C-S, Shan J-C, Chang S-S, et al. Suicide deaths among patients with end-stage renal disease receiving dialysis: a population-based retrospective cohort study of 64,000 patients in Taiwan. J Affect Disord. Feb 2018;227:7-10. [doi: 10.1016/j.jad.2017.10.020] [Medline: 29045916]
    33. Wang F, Wang Y, Tian Y, Zhang P, Chen J, Li J. Pattern recognition and prognostic analysis of longitudinal blood pressure records in hemodialysis treatment based on a convolutional neural network. J Biomed Inform. Oct 2019;98:103271. [FREE Full text] [doi: 10.1016/j.jbi.2019.103271] [Medline: 31454648]

    Have been revised to 32 and 33:

    32. Chen C, Liu C-C, Weng P-Y, Cheng Y. Mismatch Negativity to Threatening Voices Associated with Positive Symptoms in Schizophrenia. Front Hum Neurosci. 2016;10:362. [FREE Full text] [doi: 10.3389/fnhum.2016.00362] [Medline: 27471459]
    33. Wang D, Ding Y, Zhao Q, Yang P, Tan S, Li Y. ECAPA-TDNN Based Depression Detection from Clinical Speech. In Interspeech. In Interspeech. 2022;10:3333-3337. [doi: 10.21437/Interspeech.2022-10051]

    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. Chen C, Liu C-C, Weng P-Y, Cheng Y. Mismatch Negativity to Threatening Voices Associated with Positive Symptoms in Schizophrenia. Front Hum Neurosci. 2016;10:362. [FREE Full text] [CrossRef] [Medline]
    2. Wang D, Ding Y, Zhao Q, Yang P, Tan S, Li Y. ECAPA-TDNN Based Depression Detection from Clinical Speech. In Interspeech. In Interspeech. 2022;10:3333-3337. [CrossRef]

    This is a non–peer-reviewed article. submitted 29.05.25; accepted 30.05.25; published 28.07.25.

    Copyright

    ©Ramon E Diaz-Ramos, Isabella Noriega, Luis A Trejo, Eleni Stroulia, Bo Cao. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 28.07.2025.

    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 JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.