{"id":15915765,"url":"https://github.com/warvito/integrating-multi-modal-neuroimaging","last_synced_at":"2025-03-23T08:32:28.552Z","repository":{"id":101508624,"uuid":"212785743","full_name":"Warvito/integrating-multi-modal-neuroimaging","owner":"Warvito","description":"Integrating machining learning and multi-modal neuroimaging to detect schizophrenia at the level of the individual","archived":false,"fork":false,"pushed_at":"2019-10-18T09:27:45.000Z","size":67,"stargazers_count":5,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-03-18T19:29:59.423Z","etag":null,"topics":["multimodality","neuroimage","neuroimaging","schizophrenia","svm","svm-classifier"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Warvito.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-10-04T10:03:25.000Z","updated_at":"2024-01-01T06:10:10.000Z","dependencies_parsed_at":null,"dependency_job_id":"9881427f-3989-4802-a4d7-deb3d01494e2","html_url":"https://github.com/Warvito/integrating-multi-modal-neuroimaging","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Warvito%2Fintegrating-multi-modal-neuroimaging","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Warvito%2Fintegrating-multi-modal-neuroimaging/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Warvito%2Fintegrating-multi-modal-neuroimaging/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Warvito%2Fintegrating-multi-modal-neuroimaging/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Warvito","download_url":"https://codeload.github.com/Warvito/integrating-multi-modal-neuroimaging/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245078067,"owners_count":20557274,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["multimodality","neuroimage","neuroimaging","schizophrenia","svm","svm-classifier"],"created_at":"2024-10-06T17:42:13.030Z","updated_at":"2025-03-23T08:32:28.534Z","avatar_url":"https://github.com/Warvito.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Integrating machining learning and multi-modal neuroimaging to detect schizophrenia at the level of the individual\n[![MIT license](http://img.shields.io/badge/license-MIT-brightgreen.svg)](https://github.com/Warvito/integrating-multi-modal-neuroimaging/blob/master/LICENSE)\n\nOfficial script of the paper Integrating machining learning and multi-modal neuroimaging to detect schizophrenia at the level of the individual implemented by Du Lei and Walter Hugo Lopez Pinaya\n\n## Abstract\nSchizophrenia is a severe psychiatric disorder associated with both structural and\nfunctional brain abnormalities. In the past few years, there has been growing interest\nin the application of machine learning techniques to neuroimaging data for the\ndiagnostic and prognostic assessment of this disorder. However, the vast majority of\nstudies published so far have used either structural or functional neuroimaging data,\nwithout accounting for the multi-modal nature of the disorder. Structural MRI and\nresting state functional MRI data were acquired from a total of 295 patients with\nschizophrenia and 452 healthy controls at five research centers. We extracted features\nfrom the data including gray matter volume, white matter volume, amplitude of low-\nfrequency fluctuation, regional homogeneity and two connectome-wide based\nmetrics: structural covariance matrices and functional connectivity matrices. A\nsupport vector machine classifier was trained on each dataset separately to distinguish\nthe subjects at individual level using each of the single feature as well as their\ncombination, and 10-fold cross-validation approach was used to investigate the\nperformance of the model. Functional data allow higher accuracy of classification\nthan structural data (mean 82.75% vs. 75.84%). Within each modality, the\ncombination of images and matrices improves performance, resulting in mean\naccuracies of 81.63% for structural data and 87.59% for functional data. The use of all\ncombined structural and functional measures allows the highest accuracy of\nclassification (90.83%). We conclude that combining multi-modal measures within a\nsingle model is a promising direction for developing biologically-informed diagnostic\ntools in schizophrenia.\n\n\n\n## Requirements\n- Python 2\n- [Numpy](http://www.numpy.org/)\n- [Matplotlib](https://matplotlib.org/)\n- [Scikit-learn](https://scikit-learn.org/)\n\n\n## Installing the dependencies\nInstall virtualenv and creating a new virtual environment:\n\n    pip install virtualenv\n    virtualenv -p /usr/bin/python2 ./venv\n\nInstall dependencies\n\n    pip install -r requirements.txt\n\n\n## Citation\nIf you find this code useful for your research, please cite:\n\n    @article{}\n ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwarvito%2Fintegrating-multi-modal-neuroimaging","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwarvito%2Fintegrating-multi-modal-neuroimaging","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwarvito%2Fintegrating-multi-modal-neuroimaging/lists"}