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. 2023 Dec 22;25:e48244. doi: 10.2196/48244

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©Yun Kwan Kim, Ja Hyung Koo, Sun Jung Lee, Hee Seok Song, Minji Lee. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 22.12.2023.

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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Clinical interpretability results. (A) Global feature impact values produced by the proposed model. (B) Cosine similarity feature set between the non-CA and CA groups. (C) Multiresolution statistical features based on the cosine similarity matrix between the non-CA and CA groups. (D) Statistical feature set between the non-CA and CA groups. C: channel-level average; CA: cardiac arrest; Cos: cosine similarity; DBP: diastolic blood pressure; HR: heart rate; MBP: mean blood pressure; MEWS: modified early warning score; MIMIC: Medical Information Mart for Intensive Care; RR: respiratory rate; SBP: systolic blood pressure; SHAP: Shapley additive explanation; SpO2: oxyhemoglobin saturation; TEMP: temperature; W: weighted matrix.