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. 2021 Dec 6;9(12):e29225. doi: 10.2196/29225

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©Rachel S Kim, Steven Simon, Brett Powers, Amneet Sandhu, Jose Sanchez, Ryan T Borne, Alexis Tumolo, Matthew Zipse, J Jason West, Ryan Aleong, Wendy Tzou, Michael A Rosenberg. Originally published in JMIR Medical Informatics (https://medinform.jmir.org), 06.12.2021.

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 JMIR Medical Informatics, is properly cited. The complete bibliographic information, a link to the original publication on https://medinform.jmir.org/, as well as this copyright and license information must be included.

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Decision tree for rhythm-control strategy. Based on known predictors to classify rate- versus rhythm-control strategy using the training data. Maximum depth=2, minimum samples to split nodes=50.