[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-128338-en":3,"doc-seo-128338-105":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},128338,962085564549,"Genevieve","https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45",7,"Healthcare","Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis - a proof of concept study","Prosthetic valve endocarditis (PVE) is a severe complication of prosthetic valve implantation, yet current diagnostic frameworks such as the modified Duke/ESC 2015 criteria show limited sensitivity and specificity, particularly for PVE. This proof-of-concept study evaluates whether machine learning can enhance the predictive value of MDE2015 in a retrospective multicentre cohort of patients with suspected PVE, compared with the original criteria-based diagnosis.","University of Groningen  \nUsing machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis  \nten Hove, D. ; Slart, R. H.J.A. ; Glaudemans, A. W.J. M. ; Postma, D. F. ; Gomes, A. ; Swart, L. E. ; Tanis, W. ; van Geel, P. P. ; Mecozzi, G. ; Budde, R. P.J.  \nPublished in:  \nEuropean Journal of Nuclear Medicine and Molecular Imaging  \nDOI:  \n10.1007/s00259-024-06774-y  \nIMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below.  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nPublication date: 2024  \nLink to publication in University of Groningen/UMCG research database  \nCitation for published version (APA):  \nten Hove, D. , Slart, R. H. J. A. , Glaudemans, A. W. J. M. , Postma, D. F. , Gomes, A. , Swart, L. E. , Tanis, W. , van Geel, P. P. , Mecozzi, G. , Budde, R. P. J. , Mouridsen, K. , & Sinha, B. (2024) . Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis: a proof of concept study. European Journal of Nuclear Medicine  \nand Molecular Imaging, 51, 3924–3933 . [https://doi.org/10.1007/s00259-024-06774-y](https://doi.org/10.1007/s00259-024-06774-y)  \nCopyright  \nOther than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons) .  \nThe publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: [https://www.rug.nl/library/open-access/self-archiving-pure/taverne](https://www.rug.nl/library/open-access/self-archiving-pure/taverne)amendment.  \nTake-down policy  \nIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim.  \nDownloaded from the University of Groningen/U MCG research database (Pure): [http://www.rug. nl/research/portal. For technical reasons the](http://www.rug. nl/research/portal. For technical reasons the)[ ](http://www.rug. nl/research/portal. For technical reasons the)[number of authors shown on this cover page is limited to 10 maximum.](number of authors shown on this cover page is limited to 10 maximum.)  \nDownload date: 01-01-2026  \nEuropean Journal of Nuclear Medicine and Molecular Imaging (2024) 51:3924–3933  \n[https://doi.org/10.1007/s00259-024-06774-y](https://doi.org/10.1007/s00259-024-06774-y)  \nORIGINAL ARTICLE  \nUsing machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis – a proof of concept study  \nD. ten Hove1,2 · R. H. J. A. Slart1,3 · A. W. J. M. Glaudemans1 · D. F. Postma4 · A. Gomes2 · L. E. Swart5 · W. Tanis6 ·  \nP. P. van Geel7 · G. Mecozzi8 · R. P. J. Budde9 · K. Mouridsen1,10 · B. Sinha2  \nReceived: 14 November 2023 / Accepted: 17 May 2024 / Published online: 21 June 2024 © The Author(s) 2024, corrected publication 2024  \nAbstract  \nIntroduction Prosthetic valve endocarditis (PVE) is a serious complication of prosthetic valve implantation, with an estimated yearly incidence of at least 0.4-1.0% . The Duke criteria and subsequent modifications have been developed as a diagnostic framework for infective endocarditis (IE) in clinical studies. However, their sensitivity and specificity are limited, especially for PVE. Furthermore, their most recent versions (ESC2015 and ESC2023) include advanced imaging modalities, e.g., cardiac CTA and [ 18F]FDG PET/CT as major criteria. However, despite these significant changes, the weighing system using major and minor criteria","cbCaifp33NJuy2Wy","https://ap.wps.com/l/cbCaifp33NJuy2Wy","pdf",1932970,1,11,"English","en",105,"# Abstract\n## Introduction\n## Methods\n## Results\n## Discussion","[{\"question\":\"Why are the modified Duke/ESC 2015 criteria considered limited for prosthetic valve endocarditis?\",\"answer\":\"Their sensitivity and specificity are limited in clinical use, especially for PVE, and the weighing system for major and minor criteria remains unchanged despite updated ESC versions and advanced imaging modalities.\"},{\"question\":\"What machine learning models were compared in this proof-of-concept study?\",\"answer\":\"The study compared Lasso logistic regression, XGBoost-based gradient boosting decision trees, decision trees without gradient boosting, and an ensemble model combining predictions from these approaches.\"},{\"question\":\"How did the authors establish the reference (gold standard) diagnosis?\",\"answer\":\"Final PVE diagnosis was determined by endocarditis team consensus using all available clinical information, including surgical findings when performed, with at least 1 year follow-up.\"}]","Using machine learning to improve the diagnostic accuracy of the modified Duke/ESC 2015 criteria in patients with suspected prosthetic valve endocarditis - a proof of concept study | PDF",1785946936,28,{"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},"using-machine-learning-to-improve-the-diagnostic-accuracy-of-the-modified-dukeesc-2015-criteria-in-patients-with-suspected-prosthetic-valve-endocarditis-a-proof-of-concept-study","",{"@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/healthcare/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/using-machine-learning-to-improve-the-diagnostic-accuracy-of-the-modified-dukeesc-2015-criteria-in-patients-with-suspected-prosthetic-valve-endocarditis-a-proof-of-concept-study/128338/",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",[72,78,82],{"name":73,"@type":74,"acceptedAnswer":75},"Why are the modified Duke/ESC 2015 criteria considered limited for prosthetic valve endocarditis?","Question",{"text":76,"@type":77},"Their sensitivity and specificity are limited in clinical use, especially for PVE, and the weighing system for major and minor criteria remains unchanged despite updated ESC versions and advanced imaging modalities.","Answer",{"name":79,"@type":74,"acceptedAnswer":80},"What machine learning models were compared in this proof-of-concept study?",{"text":81,"@type":77},"The study compared Lasso logistic regression, XGBoost-based gradient boosting decision trees, decision trees without gradient boosting, and an ensemble model combining predictions from these approaches.",{"name":83,"@type":74,"acceptedAnswer":84},"How did the authors establish the reference (gold standard) diagnosis?",{"text":85,"@type":77},"Final PVE diagnosis was determined by endocarditis team consensus using all available clinical information, including surgical findings when performed, with at least 1 year follow-up.","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},[94,98,102,106,111,116,119,124,129,132,136],{"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":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":46,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",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"]