Application of the signature method to pattern recognition in the CEQUEL clinical trial
The classification procedure of streaming data usually requires various ad hoc methods or particular heuristic models. We explore a novel non-parametric and systematic approach to analysis of heterogeneous sequential data. We demonstrate an application of this method to classification of the delays...
| Үндсэн зохиолчид: | , , , , |
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| Формат: | Journal article |
| Хэвлэсэн: |
2016
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| _version_ | 1826310976516915200 |
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| author | Kormilitzin, A Saunders, K Harrison, P Geddes, J Lyons, T |
| author_facet | Kormilitzin, A Saunders, K Harrison, P Geddes, J Lyons, T |
| author_sort | Kormilitzin, A |
| collection | OXFORD |
| description | The classification procedure of streaming data usually requires various ad hoc methods or particular heuristic models. We explore a novel non-parametric and systematic approach to analysis of heterogeneous sequential data. We demonstrate an application of this method to classification of the delays in responding to the prompts, from subjects with bipolar disorder collected during a clinical trial, using both synthetic and real examples. We show how this method can provide a natural and systematic way to extract characteristic features from sequential data. |
| first_indexed | 2024-03-07T08:01:32Z |
| format | Journal article |
| id | oxford-uuid:14c67866-c7f1-4f9e-9b30-3b6ac683df95 |
| institution | University of Oxford |
| last_indexed | 2024-03-07T08:01:32Z |
| publishDate | 2016 |
| record_format | dspace |
| spelling | oxford-uuid:14c67866-c7f1-4f9e-9b30-3b6ac683df952023-10-04T11:31:27ZApplication of the signature method to pattern recognition in the CEQUEL clinical trialJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:14c67866-c7f1-4f9e-9b30-3b6ac683df95Symplectic Elements at Oxford2016Kormilitzin, ASaunders, KHarrison, PGeddes, JLyons, TThe classification procedure of streaming data usually requires various ad hoc methods or particular heuristic models. We explore a novel non-parametric and systematic approach to analysis of heterogeneous sequential data. We demonstrate an application of this method to classification of the delays in responding to the prompts, from subjects with bipolar disorder collected during a clinical trial, using both synthetic and real examples. We show how this method can provide a natural and systematic way to extract characteristic features from sequential data. |
| spellingShingle | Kormilitzin, A Saunders, K Harrison, P Geddes, J Lyons, T Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title | Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title_full | Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title_fullStr | Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title_full_unstemmed | Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title_short | Application of the signature method to pattern recognition in the CEQUEL clinical trial |
| title_sort | application of the signature method to pattern recognition in the cequel clinical trial |
| work_keys_str_mv | AT kormilitzina applicationofthesignaturemethodtopatternrecognitioninthecequelclinicaltrial AT saundersk applicationofthesignaturemethodtopatternrecognitioninthecequelclinicaltrial AT harrisonp applicationofthesignaturemethodtopatternrecognitioninthecequelclinicaltrial AT geddesj applicationofthesignaturemethodtopatternrecognitioninthecequelclinicaltrial AT lyonst applicationofthesignaturemethodtopatternrecognitioninthecequelclinicaltrial |