[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118760-en":3,"doc-seo-118760-105":30,"detail-sidebar-cat-0-en-105":92},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118760,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1785132997149421697",8,"Research & Report","Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning - Review","Machine learning methods are increasingly used with neuroimaging data to derive brain-based features for diagnosis and prognosis in psychiatric disorders. This review summarizes recent evaluation practices for machine learning applications in obsessive-compulsive and related disorders, and proposes a core region-based modeling strategy. By using a core set of co-altered brain regions central to underlying psychopathology, the approach supports efficient predictive modeling to distinguish symptom dimensions or clusters in individual patients. It also outlines a hypothesis-driven and data-driven route for identifying core regions across the brain, aiming for improved performance, interpretability, and generalizability.","City Research Online  \nCity, University of London Institutional Repository  \n\n| Citation: Lv, Q. , Zeljic, K. , Zhao, S. , Zhang, J. , Zhang, J. & Wang, Z. (2023) . Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning.\u003Cbr>Neuroscience Bulletin, doi: 10. 1007/s12264-023-01057-2 This is the published version of the paper.\u003Cbr>This version of the publication may differ from the final published version. |\n| --- |\n| Permanent repository link: [https://openaccess.city.ac.uk/id/eprint/30355/](https://openaccess.city.ac.uk/id/eprint/30355/)\u003Cbr>Link to published version: [https://doi.org/10.1007/s12264-023-01057-2](https://doi.org/10.1007/s12264-023-01057-2)\u003Cbr>[Copyright:](Copyright: City Research Online aims to make research outputs of City)[ City Research Online aims to make research outputs of City](Copyright: City Research Online aims to make research outputs of City), University of London available to a wider audience. Copyright and Moral Rights remain with the author(s) and/or copyright holders. URLs from City Research Online may be freely distributed and linked to.\u003Cbr>Reuse: Copies of full items can be used for personal research or study, educational, or not-for-profit purposes without prior permission or charge. Provided that the authors, title and full bibliographic details are credited, a hyperlink and/or URL is given for the original metadata page and the content isnot changed in any way. |\n\n\n| City Research Online: | [http://openaccess.city.ac.uk/](http://openaccess.city.ac.uk/) | [publications@city.ac.uk](publications@city.ac.uk) |\n| --- | --- | --- |\n|  |  |  |\n\nNeurosci. Bull.  \n[https://doi.org/10.1007/s12264-023-01057-2](https://doi.org/10.1007/s12264-023-01057-2)  \n[www.neurosci.cn](www.neurosci.cn)[ ](www.neurosci.cn)[www.springer.com/12264](www.springer.com/12264)  \nREVIEW  \nDissecting Psychiatric Heterogeneity and Comorbidity with Core Region‑Based Machine Learning  \nQian Lv1 · Kristina Zeljic2 · Shaoling Zhao3,4 · Jiangtao Zhang5 · Jianmin Zhang5 · Zheng Wang1,6  \nReceived: 2 September 2022 / Accepted: 17 February 2023  \n© The Author(s) 2023  \nAbstract Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely ‘core regions’) comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are  \n* Qian Lv [lvqian@pku.edu.cn](lvqian@pku.edu.cn)  \n* Zheng Wang [zheng.wang@pku.edu.cn](zheng.wang@pku.edu.cn)  \n1 School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China  \n2 School of Health and Psychological Sciences, City, University of London, London EC1V 0HB, UK  \n3 Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China  \n4 University of Chinese Academy of Sciences, Beijing 101408, China  \n5 Tongde Hospital of Zhejiang Province (Zhejiang Mental Health Center), Zhejiang Office of Mental Health, Hangzhou 310012, China  \n6 School of Biomedical Engineering, Hainan University, Haikou 570228, China  \nfurther introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable","cbCaidYa3524JUZZ","https://ap.wps.com/l/cbCaidYa3524JUZZ","pdf",1280054,1,20,"English","en",105,"# Abstract\n# Keywords\n# Introduction\n## Psychiatric heterogeneity and comorbidity\n## Obsessive-compulsive disorder and clinical assessment\n## Neuroimaging approaches for OCD","[{\"question\":\"What problem does the review address in psychiatric disorder research?\",\"answer\":\"It addresses how psychiatric heterogeneity and comorbidity challenge categorical diagnoses and limit precision diagnosis and personalized treatment.\"},{\"question\":\"What is the core region-based machine learning strategy proposed in the review?\",\"answer\":\"The strategy builds models using a core set of co-altered brain regions central to underlying psychopathology to improve performance, interpretability, and generalizability.\"},{\"question\":\"How does the approach help with identifying clinical symptom patterns?\",\"answer\":\"It enables efficient predictive modeling to identify distinct symptom dimensions or clusters within individual patients.\"}]","Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning - Review | PDF",1785720092,50,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":87,"head_meta":89,"extra_data":91,"updated_unix":28},"dissecting-psychiatric-heterogeneity-and-comorbidity-with-core-region-based-machine-learning-review","",{"@graph":36,"@context":86},[37,54,69],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/dissecting-psychiatric-heterogeneity-and-comorbidity-with-core-region-based-machine-learning-review/118760/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":63,"encodingFormat":61,"isAccessibleForFree":64,"interactionStatistic":65},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05","2026-08-03",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"What problem does the review address in psychiatric disorder research?","Question",{"text":76,"@type":77},"It addresses how psychiatric heterogeneity and comorbidity challenge categorical diagnoses and limit precision diagnosis and personalized treatment.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What is the core region-based machine learning strategy proposed in the review?",{"text":81,"@type":77},"The strategy builds models using a core set of co-altered brain regions central to underlying psychopathology to improve performance, interpretability, and generalizability.",{"name":83,"@type":74,"acceptedAnswer":84},"How does the approach help with identifying clinical symptom patterns?",{"text":85,"@type":77},"It enables efficient predictive modeling to identify distinct symptom dimensions or clusters within individual patients.","https://schema.org",{"og:url":52,"og:type":88,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":90,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":93},[94,98,102,106,111,115,120,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":100,"slug":101},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},"Exam",70,"exam",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},5,"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":46,"category_name":113,"show_sort_weight":29,"slug":114},6,"Technology","technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":21,"slug":126},9,"Religion & Spirituality","religion-spirituality",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":21,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":107,"slug":137},19,"General","general"]