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Discretionary Corrigenda (50)

Published on in Vol 13 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55928, first published .
Correction: A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial

Correction: A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial

Correction: A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial

Authors of this article:

Marianna Masiero1, 2 Author Orcid Image ;   Gea Elena Spada2 Author Orcid Image ;   Virginia Sanchini1 Author Orcid Image ;   Elisabetta Munzone3 Author Orcid Image ;   Ricardo Pietrobon4 Author Orcid Image ;   Lucas Teixeira4 Author Orcid Image ;   Mirtha Valencia4 Author Orcid Image ;   Aline Machiavelli4 Author Orcid Image ;   Elisa Fragale2 Author Orcid Image ;   Massimo Pezzolato1, 2 Author Orcid Image ;   Gabriella Pravettoni1, 2 Author Orcid Image
Article Authors Cited by (1) Tweetations (3) Metrics

    Corrigenda and Addenda

    1Department of Oncology and Hemato-oncology, University of Milan, Milan, Italy

    2Applied Research Division for Cognitive and Psychological Science, European Institute of Oncology IRCCS, Milan, Italy

    3Division of Medical Senology, European Institute of Oncology IRCCS, Milan, Italy

    4SporeData Inc, Durham, NC, United States

    Corresponding Author:

    Marianna Masiero, PhD

    Department of Oncology and Hemato-oncology

    University of Milan

    Via Festa del Perdono 7

    Milan, 20122

    Italy

    Phone: 39 0294372099

    Email: marianna.masiero@unimi.it



    In “A Machine Learning Model to Predict Patients’ Adherence Behavior and a Decision Support System for Patients With Metastatic Breast Cancer: Protocol for a Randomized Controlled Trial” (JMIR Res Protoc 12(1); e48852) the authors noted one error.

    In the Acknowledgments, the last sentences appeared as follows:

    The 8-item Morisky Medication Adherence Scale content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAS, LLC. The property/identifier issue/registration date/categories are as follows: US registration 5,837,273 August 20, 2019, Trade/Service Mark; US registration TX-8-285-390 June 12, 2016, Copyright; and US registration TX-8-632-533 September 21, 2018, copyright.
    This project has been funded by a Pfizer grant: Enhancing therapy adherence among patients with metastatic breast cancer (65080791).

    This has been changed to appear as follows:

    The MMAS-8 Scale, content, name, and trademarks are protected by US copyright and trademark laws. Permission for use of the scale and its coding is required. A license agreement is available from MMAR, LLC., www.moriskyscale.com.
    This project has been funded by a Pfizer grant: Enhancing therapy adherence among patients with metastatic breast cancer (65080791).

    The correction will appear in the online version of the paper on the JMIR Publications website on January 15, 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 29.12.23; accepted 29.12.23; published 15.01.24.

    Copyright

    ©Marianna Masiero, Gea Elena Spada, Virginia Sanchini, Elisabetta Munzone, Ricardo Pietrobon, Lucas Teixeira, Mirtha Valencia, Aline Machiavelli, Elisa Fragale, Massimo Pezzolato, Gabriella Pravettoni. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 15.01.2024.

    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 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.