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. 2021 Nov 23;9:649221. doi: 10.3389/fbioe.2021.649221

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Copyright © 2021 Xu, Wan, Zhao, Liu, Hong, Xiang, You, Zhou, Li, Gong, Zhu, Chen, Zhang, Gong, Li, Li, Zhang, Guo, Lai, Huang, Ting, Lin and Jin.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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Relative importance of different features of prediction for simplified model Ⅰ. These plots show the weights of the different features in the VA prediction task 1, 3, and 6 months after laser treatment for model Ⅰ. The results were stratified according to the follow-up period and the points input into the algorithms; this figure shows only the relative importance of the baseline data. The red bar indicates the average importance of the feature in the blending algorithm. (A) Feature weights in the 1-month VA prediction. (B) Feature weights in the 3-month VA prediction. (C) Feature weights in the 6-month VA prediction.