[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-127745-en":3,"doc-seo-127745-105":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},127745,962084926284,"Aurora","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals - machine learning findings from the ENIGMA OCD Working Group","White matter pathways assessed with diffusion tensor imaging have been linked to obsessive-compulsive disorder, yet generalization across sites remains unclear due to small samples and reliance on single-site studies. Classification performance was evaluated using the largest OCD DTI dataset to date, including 1336 adults and 317 pediatric participants from 18 international sites within the ENIGMA OCD Working Group. An automatic machine-learning pipeline with feature engineering, selection, and model optimization tested cross-site robustness via leave-one-site-out cross-validation.","Zurich Open Repository and Archive  \nUniversity of Zurich  \nUniversity Library Strickhofstrasse 39  \nCH-8057 Zurich [www.zora.uzh.ch](www.zora.uzh.ch)  \nYear: 2024  \nWhite matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group  \nKim, Bo-Gyeom ; Kim, Gakyung ; Abe, Yoshinari ; Alonso, Pino ; Ameis, Stephanie ; Anticevic, Alan ; Arnold, Paul D ; Balachander, Srinivas ; Banaj, Nerisa ; Bargalló, Nuria ; Batistuzzo, Marcelo C ; Benedetti, Francesco ; Bertolín, Sara ; Beucke, Jan Carl ; Bollettini, Irene ; Brem, Silvia ; Brennan, Brian P ; Buitelaar, Jan K ; Calvo, Rosa ; Castelo-Branco, Miguel ; Cheng, Yuqi ; Chhatkuli, Ritu Bhusal ; Ciullo, Valentina ; Coelho, Ana ; Couto, Beatriz ; Dallaspezia, Sara ; Ely, Benjamin A ; Ferreira, Sónia ; Fontaine, Martine ; Fouche, Jean-Paul ; Walitza,  \nSusanne ; et al  \nDOI: [https://doi.org/10.1038/s41380-023-02392-6](https://doi.org/10.1038/s41380-023-02392-6)  \nPosted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: [https://doi.org/10.5167/uzh-256963](https://doi.org/10.5167/uzh-256963)  \nJournal Article Published Version  \nThe following work is licensed under a Creative Commons: Attribution 4.0 International (CC BY 4.0) License.  \nOriginally published at:  \nKim, Bo-Gyeom; Kim, Gakyung; Abe, Yoshinari; Alonso, Pino; Ameis, Stephanie; Anticevic, Alan; Arnold, Paul D; Balachander, Srinivas; Banaj, Nerisa; Bargalló, Nuria; Batistuzzo, Marcelo C; Benedetti, Francesco; Bertolín, Sara; Beucke, Jan Carl; Bollettini, Irene; Brem, Silvia; Brennan, Brian P; Buitelaar, Jan K; Calvo, Rosa; CasteloBranco, Miguel; Cheng, Yuqi; Chhatkuli, Ritu Bhusal; Ciullo, Valentina; Coelho, Ana; Couto, Beatriz; Dallaspezia, Sara; Ely, Benjamin A; Ferreira, Sónia; Fontaine, Martine; Fouche, Jean-Paul; Walitza, Susanne; et al (2024) . White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings  \nfrom the ENIGMA OCD Working Group. Molecular Psychiatry, 29(4):1063-1074 .  \nDOI: [https://doi.org/10.1038/s41380-023-02392-6](https://doi.org/10.1038/s41380-023-02392-6)  \nMolecular [Psychiatry](Psychiatry www.nature.com/mp)[ www.nature.com/mp](Psychiatry www.nature.com/mp)  \nARTICLE OPEN   \nWhite matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group  \nBo-Gyeom Kim 1,146, Gakyung Kim2,146, Yoshinari Abe 3, Pino Alonso 4,5,6, Stephanie Ameis 7,8,9, Alan Anticevic 10, Paul D. Arnold 11,12, Srinivas Balachander 13, Nerisa Banaj 14, Nuria Bargalló15,16, Marcelo C. Batistuzzo 17,18,  \nFrancesco Benedetti 19,20, Sara Bertolín 5,21, Jan Carl Beucke22,23,24, Irene Bollettini 20, Silvia Brem25,26, Brian P. Brennan 27,28, Jan K. Buitelaar 29,30, Rosa Calvo 5,31,32,33, Miguel Castelo-Branco34,35,36, Yuqi Cheng37, Ritu Bhusal Chhatkuli38,39, Valentina Ciullo14, Ana Coelho40,41,42, Beatriz Couto40,41,42, Sara Dallaspezia43, Benjamin A. Ely 44, Sónia Ferreira40,41,42, Martine Fontaine45,  \nJean-Paul Fouche46, Rachael Grazioplene 10, Patricia Gruner10, Kristen Hagen47,48, Bjarne Hansen48,49, Gregory L. Hanna50, Yoshiyuki Hirano 38,39, Marcelo Q. Höxter17, Morgan Hough51, Hao Hu52, Chaim Huyser 53,54, Toshikazu Ikuta 55,  \nNeda Jahanshad56, Anthony James 57, Fern Jaspers-Fayer 58,59, Selina Kasprzak60,61, Norbert Kathmann22, Christian Kaufmann22, Minah Kim 62,63, Kathrin Koch 64,65, Gerd Kvale48,66, Jun Soo Kwon 63,67,68, Luisa Lazaro 5,31,32,33, Junhee Lee 62,69, Christine Lochner 70, Jin Lu71, Daniela Rodriguez Manrique64,65,72, Ignacio Martínez-Zalacaín 4,73, Yoshitada Masuda74,  \nKoji Matsumoto74, Maria Paula Maziero75,76, Jose M. Menchón 4,5,6, Luciano Minuzzi77,78, Pedro Silva Moreira 40,41,79,  \nPedro Morgado40,41,42, Janardhanan C. Narayanaswamy13, Jin Narumoto80, Ana E. Ortiz31,32,33, Junko Ota38,39, Jose C. Pariente 16, Chris Perriello81, Maria Picó-Pérez 40,41,82, Christopher","cbCaiqarjSfXC2ax","https://ap.wps.com/l/cbCaiqarjSfXC2ax","pdf",2256734,1,13,"English","en",105,"# Background\n## White matter diffusion and OCD\n# Data and Methods\n## ENIGMA OCD Working Group DTI dataset\n## Automatic machine-learning pipeline\n## Leave-one-site-out cross-validation\n# Results and Implications\n## Classification performance and generalizability","[{\"question\":\"What is the main goal of this study?\",\"answer\":\"To assess how accurately machine-learning models classify obsessive-compulsive disorder using diffusion white matter estimates, and to test whether this classification generalizes across international sites.\"},{\"question\":\"Which dataset and participant numbers were used?\",\"answer\":\"The analysis used the ENIGMA OCD Working Group DTI dataset with 1336 adults (690 OCD, 646 controls) and 317 pediatric participants (175 OCD, 142 controls) from 18 sites.\"},{\"question\":\"How was cross-site generalizability evaluated?\",\"answer\":\"Models were evaluated with leave-one-site-out cross-validation to examine performance when training and testing across different acquisition sites.\"}]","White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals - machine learning findings from the ENIGMA OCD Working Group | PDF",1785941366,33,{"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},"white-matter-diffusion-estimates-in-obsessive-compulsive-disorder-across-1653-individuals-machine-learning-findings-from-the-enigma-ocd-working-group","",{"@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/white-matter-diffusion-estimates-in-obsessive-compulsive-disorder-across-1653-individuals-machine-learning-findings-from-the-enigma-ocd-working-group/127745/",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","2026-08-22","2026-08-05",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 is the main goal of this study?","Question",{"text":76,"@type":77},"To assess how accurately machine-learning models classify obsessive-compulsive disorder using diffusion white matter estimates, and to test whether this classification generalizes across international sites.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"Which dataset and participant numbers were used?",{"text":81,"@type":77},"The analysis used the ENIGMA OCD Working Group DTI dataset with 1336 adults (690 OCD, 646 controls) and 317 pediatric participants (175 OCD, 142 controls) from 18 sites.",{"name":83,"@type":74,"acceptedAnswer":84},"How was cross-site generalizability evaluated?",{"text":85,"@type":77},"Models were evaluated with leave-one-site-out cross-validation to examine performance when training and testing across different acquisition sites.","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},[94,98,102,106,111,116,121,124,129,132,136],{"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":114,"slug":115},6,"Technology",50,"technology",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":122,"slug":123},30,"research-report",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":46,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":46,"category_name":138,"show_sort_weight":107,"slug":139},19,"General","general"]