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This protocol addresses limited evidence on whether ML adoption lowers review resource consumption and reduces time-to-completion. A retrospective study design compares recommended ML use versus no ML use, and also contrasts recommended ML use with non-recommended ML use to estimate effects quantitatively.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/the-effect-of-machine-learning-tools-for-evidence-synthesis-on-resource-use-and-time-to-completion-protocol-for-a-retrospective-pilot-study/291176/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/the-effect-of-machine-learning-tools-for-evidence-synthesis-on-resource-use-and-time-to-completion-protocol-for-a-retrospective-pilot-study/291176.png","ImageObject",300,407,{"name":92,"@type":93},"Aurelia","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-18","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the study trying to determine about machine learning in evidence synthesis?","Question",{"text":112,"@type":113},"The protocol aims to quantify whether using machine learning tools affects both resources used and time-to-completion for producing reviews.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the protocol define “recommended” versus “non-recommended” ML use?",{"text":117,"@type":113},"“Recommended” ML use refers to cases where ML replaces some human activities. “Non-recommended” ML use refers to cases where ML is over-used or under-used by being added to existing procedures rather than properly replacing tasks.",{"name":119,"@type":110,"acceptedAnswer":120},"Why is a retrospective pilot study design used?",{"text":121,"@type":113},"The protocol retrospectively includes reviews conducted at the Norwegian Institute of Public Health from 1 August 2020 onward, aligning with the first ML-using review at the institute, to compare outcomes across different ML use approaches.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},291176,1789643597,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":39,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":46,"preview_page_count":4},1099514068365,"https://ap-avatar.wpscdn.com/avatar/10000253d8d9f28188e?x-image-process=image/resize,m_fixed,w_180,h_180&k=1794309523707217728","Muller et al. Systematic Reviews (2023) 12:7 [https://doi.org/10.1186/s13643-023-02171-y](https://doi.org/10.1186/s13643-023-02171-y)  \nSystematic Reviews  \n METHODOLOGY Open Access  \nThe effect of machine learning tools for evidence synthesis on resource use and time-to-completion: protocol for a retrospective pilot study  \nAshley Elizabeth Muller 1*, Rigmor C. Berg 1, Jose Francisco Meneses‑Echavez1, Heather M. R. Ames 1, Tiril C. Borge 1, Patricia Sofia Jacobsen Jardim1, Chris Cooper2,3 and Christopher James Rose 1  \nAbstract  \nBackground Machine learning (ML) tools exist that can reduce or replace human activities in repetitive or complex tasks. Yet, ML is underutilized within evidence synthesis, despite the steadily growing rate of primary study publication and the need to periodically update reviews to reflect new evidence. Underutilization may be partially explained by a paucity of evidence on how ML tools can reduce resource use and time‑to‑completion of reviews.  \nMethods This protocol describes how we will answer two research questions using a retrospective study design: Is there a difference in resources used to produce reviews using recommended ML versus not using ML, and is there a difference in time‑to‑completion? We will also compare recommended ML use to non‑recommended ML use that merely adds ML use to existing procedures. We will retrospectively include all reviews conducted at our institute from 1 August 2020, corresponding to the commission of the first review in our institute that used ML.  \nConclusion The results of this study will allow us to quantitatively estimate the effect of ML adoption on resource use and time‑to‑completion, providing our organization and others with better information to make high‑level organizational decisions about ML.  \nHighlights  \nMachine learning (ML) tools for evidence synthesis now exist, but little is known about whether they lead to decreased resource use and time‑to‑completion of reviews.  \nWe propose a protocol to systematically measure any resource savings of using machine learning to produce evi‑ dence syntheses.  \nCo‑primary analyses will compare “recommended” ML use (in which ML replaces some human activities) and no ML use.  \nWe will additionally explore the differences between “recommended” ML use and “non‑recommended” ML use (in which ML is over‑used or under‑used) .  \n*Correspondence: Ashley Elizabeth Muller[aemu@fhi. no](aemu@fhi. no)  \nFull list of author information is available at the end of the article  \n© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit [http://creativecommons.org/licenses/by/4.0/](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[. The Creative Commons Public Domain Dedication waiver (](http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ()[http://creativeco](http://creativeco)[mmons.org/publicdomain/zero/1.0/](mmons.org/publicdomain/zero/1.0/)) applies to the data made available in this article, unless otherwise stated in a credit line to the data.  \nMuller et al. Systematic Reviews (2023) 12:7 Page 2 of 8  \nKeywords Systematic review, Machine learning, Artificial intelligence, R","cbCaigQyhNOjmBQT","https://ap.wps.com/l/cbCaigQyhNOjmBQT","pdf",1347025,"English","# Methodology\n## Open Access\n## Abstract\n## Background\n## Methods\n## Conclusion\n## Highlights\n## Keywords\n## Procedures and analysis plan","[{\"question\":\"What is the study trying to determine about machine learning in evidence synthesis?\",\"answer\":\"The protocol aims to quantify whether using machine learning tools affects both resources used and time-to-completion for producing reviews.\"},{\"question\":\"How does the protocol define “recommended” versus “non-recommended” ML use?\",\"answer\":\"“Recommended” ML use refers to cases where ML replaces some human activities. “Non-recommended” ML use refers to cases where ML is over-used or under-used by being added to existing procedures rather than properly replacing tasks.\"},{\"question\":\"Why is a retrospective pilot study design used?\",\"answer\":\"The protocol retrospectively includes reviews conducted at the Norwegian Institute of Public Health from 1 August 2020 onward, aligning with the first ML-using review at the institute, to compare outcomes across different ML use approaches.\"}]","The effect of machine learning tools for evidence synthesis on resource use and time-to-completion - protocol for a retrospective pilot study | PDF"]