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. 2021 Sep 27;11:19171. doi: 10.1038/s41598-021-98557-w

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Classification and regression tree analysis (CART) results. The first decision-making tree (a) uses two nodes of the amount of effusion in the mastoid and middle ear cavity and the presence of enhancement in the inner ear structures on post-contrast T1-weighted images (postT1WI). The second decision-making tree (b) utilized the degree of enhancement in the inner ear structures on post-contrast FLAIR images (postFLAIR) as the partitioning node. Group A was the chronic otitis media (COM) group, group B was the autoimmune inner ear disease and autoinflammatory inner ear disease (AIED/AID) group, and group C was the control group. The details regarding the tree are explained in the “Results” section.