[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125334-en":3,"doc-seo-125334-105":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},125334,962075114765,"Quinn","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Machine learning approach for automated localization of ventricular tachycardia ablation targets from substrate maps - development and validation in a porcine model","Ventricular tachycardia (VT) recurs at a high rate after ablation because locating VT critical sites remains difficult. This study develops a machine learning method to improve identification of ablation targets using intracardiac electrogram (EGM) features derived from standard substrate mapping. In a chronic myocardial infarction porcine model, 13 pigs underwent invasive electrophysiological studies, collecting 56 substrate maps and 35,068 EGMs during sinus rhythm and pacing, followed by VT induction and localization to evaluate model performance.","King’s Research Portal  \nDOI:  \n10.1093/ehjdh/ztaf064  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nLink to publication record in King's Research Portal  \nCitation for published version (APA):  \nWang, X. , Dennis, A. , Hesselkilde, E. M. , Saljic, A. , Linz, B. M. , Sattler, S. M. , Williams, J. , Tfelt-Hansen, J. , Jespersen, T. , Chow, A. W. C. , Dhanjal, T. , Lambiase, P. D. , & Orini, M. (2025) . Machine learning approach for automated localization of ventricular tachycardia ablation targets from substrate maps: development and validation in a porcine model. European Heart Journal Digital Health, 6(4), 645-655.  \n[https://doi.org/10.1093/ehjdh/ztaf064](https://doi.org/10.1093/ehjdh/ztaf064)  \nCiting this paper  \nPlease note that where the full-text provided on King's Research Portal is the Author Accepted Manuscript or Post-Print version this may differ from the final Published version. If citing, it is advised that you check and use the publisher's definitive version for pagination, volume/issue, and date of publication details. And where the final published version is provided on the Research Portal, if citing you are again advised to check the publisher's website for any subsequent corrections.  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the Research Portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognize and abide by the legal requirements associated with these rights.  \n•Users may download and print one copy of any publication from the Research Portal for the purpose of private study or research.  \n•You may not further distribute the material or use it for any profit-making activity or commercial gain  \n•You may freely distribute the URL identifying the publication in the Research Portal  \nTake down policy  \nIf you believe that this document breaches copyright please contact [librarypure@kcl.ac.uk](librarypure@kcl.ac.uk) providing details, and we will remove access to the work immediately and investigate your claim.  \nDownload date: 25. Sep. 2025  \nEuropean Heart Journal-Digital Health (2025) 6, 645–655  \nORIGINAL ARTICLE  \n[https://doi.org/10.1093/ehjdh/ztaf064](https://doi.org/10.1093/ehjdh/ztaf064 Artificial intelligence)[ Artificial intelligence](https://doi.org/10.1093/ehjdh/ztaf064 Artificial intelligence) (machine learning, deep learning)  \nMachine learning approach for automated localization of ventricular tachycardia ablation targets from substrate maps: development and validation in a porcine model  \nXuezhe Wang  1,†, Adam Dennis1, Eva Melis Hesselkilde2, Arnela Saljic  2, Benedikt M. Linz2, Stefan M. Sattler2,3, James Williams4, Jacob Tfelt-Hansen3,5, Thomas Jespersen  2, Anthony W.C. Chow6, Tarvinder Dhanjal  7,  \nPier D. Lambiase1,6,†, and Michele Orini  1,8,*†  \n1Institute of Cardiovascular Science, University College London, 1-19 Torrington Pl, London WC1E 7HB, UK; 2Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 3Department of Cardiology, Heart Centre Copenhagen University Hospital, Copenhagen, Denmark; 4Abbott Medical United Kingdom, Blythe Valley Park, Solihull, UK; 5Department of Forensic Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 6Barts Heart Centre, Barts Health NHS Trust, London, UK; 7University of Warwick, University Hospital Coventry & Warwickshire, UK; and 8School of Biomedical Engineering & Imaging Sciences, King’s College London, UK  \nReceived 11 February 2025; revised 7 April 2025; accepted 12 May 2025; online publish-ahead-of-print 10 June 2025  \nAims The recurrence rate of ventricular tachycardia (VT) after ablation remains high due to the difficulty in locating VT critical  \nsites. This study proposes a machine learning approach for improved identification of ablation targets based on intracardiac electrograms (EGMs) f","cbCaikvJb3iABSWK","https://ap.wps.com/l/cbCaikvJb3iABSWK","pdf",1101724,1,12,"English","en",105,"# Aims\n# Methods and results\n## Data acquisition and feature computation\n## Model development and performance\n# Conclusion","[{\"question\":\"What problem does the study address in ventricular tachycardia ablation?\",\"answer\":\"The study targets the high recurrence rate after VT ablation caused by difficulty in locating VT critical sites.\"},{\"question\":\"How were ablation targets localized and evaluated?\",\"answer\":\"After inducing VT in chronic MI pigs, the study localized and mapped VT circuits, then treated mapping sites within 6 mm of critical sites as potential ablation targets.\"},{\"question\":\"Which machine learning model performed best and on what data?\",\"answer\":\"Random forest provided the best accuracy using unipolar signals from the sinus rhythm map, with an area under the curve of 0.821 and sensitivity/specificity of 81.4%/71.4%.\"}]","Machine learning approach for automated localization of ventricular tachycardia ablation targets from substrate maps - development and validation in a porcine model | PDF",1785898239,30,{"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},"machine-learning-approach-for-automated-localization-of-ventricular-tachycardia-ablation-targets-from-substrate-maps-development-and-validation-in-a-porcine-model","",{"@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/machine-learning-approach-for-automated-localization-of-ventricular-tachycardia-ablation-targets-from-substrate-maps-development-and-validation-in-a-porcine-model/125334/",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 problem does the study address in ventricular tachycardia ablation?","Question",{"text":75,"@type":76},"The study targets the high recurrence rate after VT ablation caused by difficulty in locating VT critical sites.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How were ablation targets localized and evaluated?",{"text":80,"@type":76},"After inducing VT in chronic MI pigs, the study localized and mapped VT circuits, then treated mapping sites within 6 mm of critical sites as potential ablation targets.",{"name":82,"@type":73,"acceptedAnswer":83},"Which machine learning model performed best and on what data?",{"text":84,"@type":76},"Random forest provided the best accuracy using unipolar signals from the sinus rhythm map, with an area under the curve of 0.821 and sensitivity/specificity of 81.4%/71.4%.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"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":29,"slug":121},"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"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":106,"slug":137},19,"General","general"]