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. 2024 May 15;110(9):5545–5562. doi: 10.1097/JS9.0000000000001650

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Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc.

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0/

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Machine learning was used to compare the importance ranking of each independent influencing factor in predicting the Glasgow Outcome Scale in traumatic brain injury patients. (A) The importance ranking based on the coagulopathy model was obtained by machine learning in the training group. (B) The importance ranking based on the X1 model was obtained by machine learning in the training group. (C) The importance ranking based on the coagulopathy model was obtained by machine learning in the validation group. (D) The importance ranking based on the X1 model was obtained by machine learning in the validation group.