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. 2022 Aug 10;16:960350. doi: 10.3389/fnhum.2022.960350

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Copyright © 2022 Lu, Zhang, Yan, Mansouri, Tanglay, Osipowicz, Joyce, Young, Zhang, Doyen, Sughrue and He.

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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Machine learning modeling to classify subjects into Insomnia disorder and controls. (A) The functional connectivity among 39 brain regions comprised the top 20 features of the model, depicted here in a SHAP plot. The x-axis depicts the impact of each feature on the model output, while the color of each data point indicates whether a high or low functional connectivity is associated with the output. (B) The regions are demonstrated on a model brain. (C) The graph demonstrates the mean importance of each network on the model’s classification.