Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification
Purposes Studies of brain networks in schizophrenia (SCZ) have shown that both structural and functional networks are altered in patients. Extracting accurate discriminative features from brain networks as classification features can improve the classification accuracy of SCZ and avoid the deficienc...
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| Format: | Article |
| Language: | English |
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Editorial Office of Journal of Taiyuan University of Technology
2023-09-01
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| Series: | Taiyuan Ligong Daxue xuebao |
| Subjects: | |
| Online Access: | https://tyutjournal.tyut.edu.cn/englishpaper/show-2116.html |
| _version_ | 1827283416016486400 |
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| author | Pengfei YANG Jiayue XUE Bin WANG Shuhong WU |
| author_facet | Pengfei YANG Jiayue XUE Bin WANG Shuhong WU |
| author_sort | Pengfei YANG |
| collection | DOAJ |
| description | Purposes Studies of brain networks in schizophrenia (SCZ) have shown that both structural and functional networks are altered in patients. Extracting accurate discriminative features from brain networks as classification features can improve the classification accuracy of SCZ and avoid the deficiencies caused by subjective diagnosis relying on scales. Traditional brain network features such as betweenness centrality and clustering coefficients lose topological information, and minimum spanning tree loses some brain region connections. Although subgraphs retain topological information, the screening of traditional discriminative subgraphs generates some redundant information, which in turn affects the classification accuracy. Methods In this paper, a screening method for discriminant subgraphs based on frequency ranking (Frequency Scoring Screen, FSS) is propsed. FSS screens discriminative subgraphs and eliminates redundant information without losing the original discriminative information. The classification performance of using different features and different classification algorithms is compared by using publicly available data from OpenfMRI. Findings The results show that the classification performance of the FSS feature is better than that of other traditional brain network features, the feature is not affected by the classification algorithm, and the classification accuracy is better than existing SCZ classification literatures. |
| first_indexed | 2024-04-24T09:36:07Z |
| format | Article |
| id | doaj.art-19aa28ad0c4a4c11b767abf54629688d |
| institution | Directory Open Access Journal |
| issn | 1007-9432 |
| language | English |
| last_indexed | 2024-04-24T09:36:07Z |
| publishDate | 2023-09-01 |
| publisher | Editorial Office of Journal of Taiyuan University of Technology |
| record_format | Article |
| series | Taiyuan Ligong Daxue xuebao |
| spelling | doaj.art-19aa28ad0c4a4c11b767abf54629688d2024-04-15T09:17:01ZengEditorial Office of Journal of Taiyuan University of TechnologyTaiyuan Ligong Daxue xuebao1007-94322023-09-0154584685210.16355/j.tyut.1007-9432.2023.05.0121007-9432(2023)05-0846-07Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia ClassificationPengfei YANG0Jiayue XUE1Bin WANG2Shuhong WU3College of Information and Computer, Taiyuan University of Technology, Jinzhong 030600, ChinaCollege of Information and Computer, Taiyuan University of Technology, Jinzhong 030600, ChinaCollege of Information and Computer, Taiyuan University of Technology, Jinzhong 030600, ChinaCollege of Information and Computer, Taiyuan University of Technology, Jinzhong 030600, ChinaPurposes Studies of brain networks in schizophrenia (SCZ) have shown that both structural and functional networks are altered in patients. Extracting accurate discriminative features from brain networks as classification features can improve the classification accuracy of SCZ and avoid the deficiencies caused by subjective diagnosis relying on scales. Traditional brain network features such as betweenness centrality and clustering coefficients lose topological information, and minimum spanning tree loses some brain region connections. Although subgraphs retain topological information, the screening of traditional discriminative subgraphs generates some redundant information, which in turn affects the classification accuracy. Methods In this paper, a screening method for discriminant subgraphs based on frequency ranking (Frequency Scoring Screen, FSS) is propsed. FSS screens discriminative subgraphs and eliminates redundant information without losing the original discriminative information. The classification performance of using different features and different classification algorithms is compared by using publicly available data from OpenfMRI. Findings The results show that the classification performance of the FSS feature is better than that of other traditional brain network features, the feature is not affected by the classification algorithm, and the classification accuracy is better than existing SCZ classification literatures.https://tyutjournal.tyut.edu.cn/englishpaper/show-2116.htmlschizophreniastructural and functional networksfeature selectiondiscriminative subgraphclassification |
| spellingShingle | Pengfei YANG Jiayue XUE Bin WANG Shuhong WU Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification Taiyuan Ligong Daxue xuebao schizophrenia structural and functional networks feature selection discriminative subgraph classification |
| title | Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification |
| title_full | Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification |
| title_fullStr | Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification |
| title_full_unstemmed | Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification |
| title_short | Discriminant Subgraph Screening Based on Frequency Sorting and Its Application to Schizophrenia Classification |
| title_sort | discriminant subgraph screening based on frequency sorting and its application to schizophrenia classification |
| topic | schizophrenia structural and functional networks feature selection discriminative subgraph classification |
| url | https://tyutjournal.tyut.edu.cn/englishpaper/show-2116.html |
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