[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128156-en":3,"doc-seo-128156-105":30,"detail-sidebar-cat-0-en-105":84},{"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},128156,549768072016,"River Wang","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","HUMANE - Harmonious Understanding of Machine Learning Analytics Network - global consensus for research on artificial intelligence in medicine","AI research, development, and implementation are accelerating rapidly across healthcare, creating higher demand for clinical outcomes while exposing a major gap in AI literacy for clinicians and researchers. This shortage also limits practical tools for building a structured literature framework in AI in medicine. HUMANE (Harmonious Understanding of Machine Learning Analytics Network) provides a checklist designed to establish an international consensus for authors and reviewers working on AI/ML in medicine.","Exploration of Digital Health Technologies  \nOpen Access Original Article  \nHUMANE: Harmonious Understanding of Machine Learning Analytics Network—global consensus for research on artificial intelligence in medicine  \nNeha Deo1†, Faisal A. Nawaz2†, Clea du Toit3 , Tran Tran3, Chaitanya Mamillapalli4 , Piyush Mathur5 , Sandeep Reddy6 , Shyam Visweswaran7 , Thanga Prabhu8, Khalid Moidu9 , Sandosh  \nPadmanabhan3 , Rahul Kashyap10,11*   \n1Massachusetts General Hospital, Boston, MA 02114, USA  \n2Al Amal Psychiatric Hospital, Emirates Health Services, Dubai 2299, United Arab Emirates 3School of Cardiovascular and Metabolic Health, University of Glasgow, G12 8TA Glasgow, UK 4Department of Endocrinology, Springfield Clinic, Springfield, IL 62702-5104, USA 5Department of Anesthesiology, Cleveland Clinic, Cleveland, OH 44195, USA  \n6Chair, Healthcare Operations, Deakin University, Geelong, VIC 3216, Australia  \n7Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15206-3701, USA 8Chief Medical Information Officer, Apollo Hospitals, Chennai 600006, TN, India  \n9Chief Information Officer Consultant, Orlando, FL, USA  \n10Department of Anesthesiology and Critical Care Medicine, Mayo Clinic, Rochester, MN 55905, USA 11Department of Research, WellSpan Health, York, PA 17403, USA  \n†These authors contributed equally to this work.  \n†These authors contributed equally to this work.  \n*Correspondence: Rahul Kashyap, Department of Anesthesiology and Critical Care Medicine, Mayo Clinic, 200 First St SW, Rochester, MN 55905, [USA.](USA. kashyapmd@gmail.com)[ kashyapmd@gmail.com](USA. kashyapmd@gmail.com)  \n[Academic Editor:](Academic Editor: Zhaohui Gong)[ Zhaohui Gong](Academic Editor: Zhaohui Gong), Ningbo University, China  \nReceived: February 19, 2024 Accepted: May 15, 2024 Published: June 30, 2024  \nCite this article: Deo N, Nawaz FA, du Toit C, Tran T, Mamillapalli C, Mathur P, et al. HUMANE: Harmonious Understanding of Machine Learning Analytics Network—global consensus for research on artificial intelligence in medicine. Explor Digit Health Technol. 2024;2:157–66. [https://doi.org/10.37349/edht.2024.00018](https://doi.org/10.37349/edht.2024.00018)  \nAbstract  \nAim: AI research, development, and implementation are expanding at an exponential pace across healthcare. This paradigm shift in healthcare research has led to increased demands for clinical outcomes, all at the expense of a significant gap in AI literacy within the healthcare field. This has further translated toa lack of tools in creating a framework for literature in the AI in medicine domain. We propose HUMANE (Harmonious Understanding of Machine Learning Analytics Network), a checklist for establishing an international consensus for authors and reviewers involved in research focused on artificial intelligence (AI) or machine learning (ML) in medicine.  \nMethods: This study was conducted using the Delphi method by devising a survey using the Google Forms platform. The survey was developed as a checklist containing 8 sections and 56 questions with a 5-point Likert scale.  \nResults: A total of 33 survey respondents were part of the initial Delphi process with the majority (45%) in the 36–45 years age group. The respondents were located across the USA (61%), UK (24%), and Australia  \n© The Author(s) 2024. This is an Open Access article licensed under a Creative Commons Attribution 4.0 International License ([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)), which permits unrestricted use, sharing, adaptation, distribution and reproduction in any medium or format, for any purpose, even commercially, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.  \nExplor Digit Health Technol. 2024;2:157–66 | [https://doi.org/10.37349/edht.2024.00018](https://doi.org/10.37349/edht.2024.00018) Page 157  \n(9%) as the top","cbCaivxrFkPNPVwG","https://ap.wps.com/l/cbCaivxrFkPNPVwG","pdf",1830041,1,10,"English","en",105,"# Abstract\n## Aim\n## Methods\n## Results\n## Conclusions\n# Introduction\n## Artificial intelligence in healthcare growth\n## Examples of AI impact\n## Motivation for consensus checklist","[{\"question\":\"What does the study conclude about the potential of HUMANE?\",\"answer\":\"The HUMANE international consensus reflects on further research into how the checklist can improve the reliability and quality of AI/ML research in medicine.\"}]","HUMANE - Harmonious Understanding of Machine Learning Analytics Network - global consensus for research on artificial intelligence in medicine | PDF",1785945150,25,{"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":79,"head_meta":81,"extra_data":83,"updated_unix":28},"humane-harmonious-understanding-of-machine-learning-analytics-network-global-consensus-for-research-on-artificial-intelligence-in-medicine","",{"@graph":36,"@context":78},[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/humane-harmonious-understanding-of-machine-learning-analytics-network-global-consensus-for-research-on-artificial-intelligence-in-medicine/128156/",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","2026-08-23","2026-08-05",true,{"@type":66,"interactionType":67,"userInteractionCount":20},"InteractionCounter",{"@type":68},"ViewAction",{"@type":70,"mainEntity":71},"FAQPage",[72],{"name":73,"@type":74,"acceptedAnswer":75},"What does the study conclude about the potential of HUMANE?","Question",{"text":76,"@type":77},"The HUMANE international consensus reflects on further research into how the checklist can improve the reliability and quality of AI/ML research in medicine.","Answer","https://schema.org",{"og:url":52,"og:type":80,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":82,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":85},[86,90,94,98,103,108,113,116,121,124,127],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":87,"show_sort_weight":88,"slug":89},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":91,"show_sort_weight":92,"slug":93},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":95,"show_sort_weight":96,"slug":97},"Exam",70,"exam",{"id":99,"doc_module":4,"doc_module_name":46,"category_name":100,"show_sort_weight":101,"slug":102},5,"Comic",60,"comic",{"id":104,"doc_module":4,"doc_module_name":46,"category_name":105,"show_sort_weight":106,"slug":107},6,"Technology",50,"technology",{"id":109,"doc_module":4,"doc_module_name":46,"category_name":110,"show_sort_weight":111,"slug":112},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":114,"slug":115},30,"research-report",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":118,"show_sort_weight":119,"slug":120},9,"Religion & Spirituality",20,"religion-spirituality",{"id":119,"doc_module":4,"doc_module_name":46,"category_name":122,"show_sort_weight":119,"slug":123},"World Cup","world-cup",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":21,"slug":126},"Lifestyle","lifestyle",{"id":128,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":99,"slug":130},19,"General","general"]