[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124932-en":3,"doc-seo-124932-105":30,"detail-sidebar-cat-0-en-105":91},{"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":4,"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},124932,5909877438554,"Maeve","https://ap-avatar.wpscdn.com/avatar/5600025385ad2bf12a7?_k=1778553567797529272",8,"Research & Report","Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders - a machine learning evaluation","The study evaluates and predicts the long-term effectiveness of five lifestyle interventions for people with eating disorders using machine learning. Participants were diagnosed using the Eating Disorder Diagnostic Scale and measures of body composition, metabolic and lipid outcomes were collected at baseline, during, and at intervention end. Random Forest and Gradient Boosting models, after feature engineering and dataset balancing, achieved high predictive accuracy. Predicted effectiveness ranked counseling with exercise and diet highest, followed by aerobic exercise with diet, walking with diet, flexible diet exercise, and online program-based exercise.","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  \nPredicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: a machine learning  \nevaluation  \nIrandoust, Khadijeh ; Parsakia, Kamdin ; Estifa, Ali ; Zoormand, Gholamreza ; Knechtle, Beat ; Rosemann,  \nThomas ; Weiss, Katja ; Taheri, Morteza  \nDOI: [https://doi.org/10.3389/fnut.2024.1390751](https://doi.org/10.3389/fnut.2024.1390751)  \nPosted at the Zurich Open Repository and Archive, University of Zurich ZORA URL: [https://doi.org/10.5167/uzh-262952](https://doi.org/10.5167/uzh-262952)  \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:  \nIrandoust, Khadijeh; Parsakia, Kamdin; Estifa, Ali; Zoormand, Gholamreza; Knechtle, Beat; Rosemann, Thomas; Weiss, Katja; Taheri, Morteza (2024) . Predicting and comparing the long-term impact of lifestyle interventionson individuals with eating disorders in active population: a machine learning evaluation. Frontiers in Nutrition, 11:1390751 .  \nDOI: [https://doi.org/10.3389/fnut.2024.1390751](https://doi.org/10.3389/fnut.2024.1390751)  \nOPEN ACCESS  \nEDITED BY  \nAlessandra Pokrajac-Bulian, University of Rijeka, Croatia  \nREVIEWED BY  \nAlexandre Puttick,  \nBern University of Applied Sciences, Switzerland  \nPetra Anić,  \nUniversity of Rijeka, Croatia Yu Wang,  \nSichuan University, China  \n*CORRESPONDENCE  \nKhadijeh Irandoust  \n [irandoust@ikiu.ac.ir](irandoust@ikiu.ac.ir)[ ](irandoust@ikiu.ac.ir)Beat Knechtle  \n beat. knechtle@hispeed.ch  \nRECEIVED 23 February 2024  \nACCEPTED 15 July 2024  \nPUBLISHED 07 August 2024  \nCITATION  \nIrandoust K, Parsakia K, Estifa A, Zoormand G, Knechtle B, Rosemann T, Weiss K and  \nTaheri M (2024) Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: a machine learning evaluation.  \nFront. Nutr. 11:1390751 .  \ndoi: 10.3389/fnut.2024.1390751  \nCOPYRIGHT  \n© 2024 Irandoust, Parsakia, Estifa, Zoormand, Knechtle, Rosemann, Weiss and Taheri. This isan open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.  \nTYPE Original Research PUBLISHED 07 August 2024 DOI 10.3389/fnut.2024.1390751  \nPredicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders in active population: a machine learning evaluation  \nKhadijeh Irandoust 1*, Kamdin Parsakia 2, Ali Estifa 1, Gholamreza Zoormand3, Beat Knechtle4*, Thomas Rosemann 5, Katja Weiss 5 and Morteza Taheri 6  \n1 Department of Sport Sciences, Imam Khomeini International University, Qazvin, Iran, 2 Department of Psychology and Counseling, KMAN Research Institute, Richmond Hill, ON, Canada, 3 Department of Physical Education, Huanggang Normal University, Huanggang, China, 4 Medbase St. Gallen Am Vadianplatz, St. Gallen, Switzerland, 5 Institute of Primary Care, University of Zürich, Zürich, Switzerland, 6 Department of Cognitive and Behavioural Sciences in Sport, Faculty of Sport Science and Health, University of Tehran, Tehran, Iran  \nObjective: This study aims to evaluate and predict the long-term effectiveness of five lifestyle interventions for individuals with eating disorders using machine learning techniques.  \nMethods: This study, conducted at Dr. Irandoust’s Health Center at Qazvin from August 2021 to August 2023, aimed to evaluate the effects of five lifestyle intervention","cbCaia1rrj0vkq4b","https://ap.wps.com/l/cbCaia1rrj0vkq4b","pdf",1068107,1,14,"English","en",105,"# Objective\n## Methods\n## Results\n## Conclusion","[{\"question\":\"What is the main objective of the study?\",\"answer\":\"To evaluate and predict the long-term effectiveness of five lifestyle interventions for individuals with eating disorders using machine learning techniques.\"},{\"question\":\"Which interventions were compared in the study?\",\"answer\":\"The interventions were counseling with exercise and dietary regime; aerobic exercise with dietary regime; walking with dietary regime; exercise with a flexible diet; and exercises through online programs and applications.\"},{\"question\":\"What machine learning models were used and how accurate were they?\",\"answer\":\"Random Forest and Gradient Boosting Regressors were used. Accuracy reached about 85% and 89%, and then about 89% and 90% after dataset balancing.\"}]","Predicting and comparing the long-term impact of lifestyle interventions on individuals with eating disorders - a machine learning evaluation | PDF",1785895453,35,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"predicting-and-comparing-the-long-term-impact-of-lifestyle-interventions-on-individuals-with-eating-disorders-a-machine-learning-evaluation","",{"@graph":36,"@context":85},[37,54,68],{"@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/predicting-and-comparing-the-long-term-impact-of-lifestyle-interventions-on-individuals-with-eating-disorders-a-machine-learning-evaluation/124932/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-05",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What is the main objective of the study?","Question",{"text":75,"@type":76},"To evaluate and predict the long-term effectiveness of five lifestyle interventions for individuals with eating disorders using machine learning techniques.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which interventions were compared in the study?",{"text":80,"@type":76},"The interventions were counseling with exercise and dietary regime; aerobic exercise with dietary regime; walking with dietary regime; exercise with a flexible diet; and exercises through online programs and applications.",{"name":82,"@type":73,"acceptedAnswer":83},"What machine learning models were used and how accurate were they?",{"text":84,"@type":76},"Random Forest and Gradient Boosting Regressors were used. 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