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Categorizing SHR and WKY rats by chi2 algorithm and decision tree

Classifying mental disorder is a big issue in psychology in recent years. This article focuses on offering a relation between decision tree and encoding of fMRI that can simplify the analysis of different mental disorders and has a high ROC over 0.9. Here we encode fMRI information to the power-law...

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Autores principales: Tsai, Ping-Rui, Chen, Kun-Huang, Hong, Tzay-Ming, Wang, Fu-Nien, Huang, Teng-Yi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876131/
https://www.ncbi.nlm.nih.gov/pubmed/33568725
http://dx.doi.org/10.1038/s41598-021-82864-3
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author Tsai, Ping-Rui
Chen, Kun-Huang
Hong, Tzay-Ming
Wang, Fu-Nien
Huang, Teng-Yi
author_facet Tsai, Ping-Rui
Chen, Kun-Huang
Hong, Tzay-Ming
Wang, Fu-Nien
Huang, Teng-Yi
author_sort Tsai, Ping-Rui
collection PubMed
description Classifying mental disorder is a big issue in psychology in recent years. This article focuses on offering a relation between decision tree and encoding of fMRI that can simplify the analysis of different mental disorders and has a high ROC over 0.9. Here we encode fMRI information to the power-law distribution with integer elements by the graph theory in which the network is characterized by degrees that measure the number of effective links exceeding the threshold of Pearson correlation among voxels. When the degrees are ranked from low to high, the network equation can be fit by the power-law distribution. Here we use the mentally disordered SHR and WKY rats as samples and employ decision tree from chi2 algorithm to classify different states of mental disorder. This method not only provides the decision tree and encoding, but also enables the construction of a transformation matrix that is capable of connecting different metal disorders. Although the latter attempt is still in its fancy, it may have a contribution to unraveling the mystery of psychological processes.
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spelling pubmed-78761312021-02-11 Categorizing SHR and WKY rats by chi2 algorithm and decision tree Tsai, Ping-Rui Chen, Kun-Huang Hong, Tzay-Ming Wang, Fu-Nien Huang, Teng-Yi Sci Rep Article Classifying mental disorder is a big issue in psychology in recent years. This article focuses on offering a relation between decision tree and encoding of fMRI that can simplify the analysis of different mental disorders and has a high ROC over 0.9. Here we encode fMRI information to the power-law distribution with integer elements by the graph theory in which the network is characterized by degrees that measure the number of effective links exceeding the threshold of Pearson correlation among voxels. When the degrees are ranked from low to high, the network equation can be fit by the power-law distribution. Here we use the mentally disordered SHR and WKY rats as samples and employ decision tree from chi2 algorithm to classify different states of mental disorder. This method not only provides the decision tree and encoding, but also enables the construction of a transformation matrix that is capable of connecting different metal disorders. Although the latter attempt is still in its fancy, it may have a contribution to unraveling the mystery of psychological processes. Nature Publishing Group UK 2021-02-10 /pmc/articles/PMC7876131/ /pubmed/33568725 http://dx.doi.org/10.1038/s41598-021-82864-3 Text en © The Author(s) 2021 Open AccessThis 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/.
spellingShingle Article
Tsai, Ping-Rui
Chen, Kun-Huang
Hong, Tzay-Ming
Wang, Fu-Nien
Huang, Teng-Yi
Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title_full Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title_fullStr Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title_full_unstemmed Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title_short Categorizing SHR and WKY rats by chi2 algorithm and decision tree
title_sort categorizing shr and wky rats by chi2 algorithm and decision tree
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7876131/
https://www.ncbi.nlm.nih.gov/pubmed/33568725
http://dx.doi.org/10.1038/s41598-021-82864-3
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