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. 2021 Nov 2;23(11):e28999. doi: 10.2196/28999

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©Hansapani Rodrigo, Eldré W Beukes, Gerhard Andersson, Vinaya Manchaiah. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 02.11.2021.

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, 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.

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The best classification and regression tree decision tree model. The fitted tree has 10 terminal nodes (denote the decision criteria). The variable categories (please refer to Multimedia Appendix 2 for variable category labels) corresponding to each split are given at the top of each branch. Each terminal node contains the predicted treatment class ("1" indicates the successful treatment class and "0" indicates the unsuccessful treatment class), the percentage of subjects with successful treatment outcomes, and the percentage of participants with the given characteristics in the training set.