[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121097-en":3,"doc-seo-121097-105":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},121097,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Interpretable Machine Learning in Endocrinology - A Diagnostic Tool in Primary Aldosteronism","Urinary steroid metabolomics combined with machine learning is presented as an approach for detecting and performing differential diagnosis of Primary Aldosteronism. The work focuses on applying a prototype-based Generalized Matrix Relevance Learning Vector Quantization model to classify steroid metabolomics profiles. The method supports successful diagnosis of Primary Aldosteronism and highlights the contribution of available biomarkers, while enabling non-invasive identification of a subtype linked to an adrenal adenoma-associated mutation.","University of Groningen  \nInterpretable Machine Learning in Endocrinology  \nBiehl, Michael; Pavlov, David; Sitch, Alice J. ; Prete, Alessandro; Arlt, Wiebke  \nPublished in:  \nAdvances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond  \nDOI:  \n10. 1007/978-3-031-67159-3_ 11  \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):  \nBiehl, M. , Pavlov, D. , Sitch, A. J. , Prete, A. , & Arlt, W. (2024) . Interpretable Machine Learning in Endocrinology: A Diagnostic Tool in Primary Aldosteronism. In T. Villmann, M. Kaden, T. Geweniger, & F.-M. Schleif (Eds.), Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (pp. 96-105) . (Lecture Notes in Networks and Systems; Vol. 1087) . Springer.  \n[https://doi.org/10.1007/978-3-031-67159-3_1](https://doi.org/10.1007/978-3-031-67159-3_1)1  \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: 29-12-2025  \nInterpretable Machine Learning in Endocrinology: A Diagnostic Tool in Primary Aldosteronism  \nMichael Biehl 1,2(B), David Pavlov 1 , Alice J. Sitch3,4 , Alessandro Prete3,5,6, and Wiebke Arlt7,8  \n1 Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence,  \nUniversity of Groningen, Groningen, The Netherlands [m.biehl@rug.nl](m.biehl@rug.nl)  \n2 Centre for Systems Modelling and Quantitative Biomedicine,  \nUniversity of Birmingham, Birmingham, UK  \n3 NIHR Birmingham Biomedical Research Centre, University of Birmingham  \nand University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK {a.j.sitch,[a.prete}@bham.ac.uk](a.prete}@bham.ac.uk)  \n4 Institute of Applied Health Research, University of Birmingham, Birmingham, UK  \n5 Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK  \n6 Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK  \n7 Medical Research Council Laboratory of Medical Sciences, London, UK  \n[w.arlt@lms.mrc.ac.uk](w.arlt@lms.mrc.ac.uk)  \n8 Institute of Clinical Sciences, Faculty of Medicine, Imperial College London,  \nLondon, UK  \nAbstract. The use of urinary steroid metabolomics (USM) in combination with machine learning in endocrinology is briefly introduced. We demonstrate the usefulness of the approach for the detection and differential diagnosis of Primary Aldosteronism (PA), which has been addressed in a recent retrospective study. Here, we mainly present res","cbCailXcIIszYRlW","https://ap.wps.com/l/cbCailXcIIszYRlW","pdf",1445412,1,11,"English","en",105,"# Introduction, Background and Motivation\n## Role of adrenal glands in endocrine regulation\n## Urinary Steroid Metabolomics and interpretable ML for diagnosis\n# Interpretable machine learning approach\n## Prototype-based GMLR-LVQ classification\n## Biomarker insights and subtype identification","[{\"question\":\"What data type does the approach use for diagnosing Primary Aldosteronism?\",\"answer\":\"It uses urinary steroid metabolomics (USM), analyzing steroid metabolite excretion profiles in urine to support diagnosis.\"},{\"question\":\"Which machine learning method is highlighted in this contribution?\",\"answer\":\"The results focus on a prototype-based Generalized Matrix Relevance Learning Vector Quantization (GMLR-LVQ) model for classification of metabolomics profiles.\"},{\"question\":\"How does the method contribute beyond classification?\",\"answer\":\"It provides insights into the importance of available markers and enables non-invasive identification of a subtype of Primary Aldosteronism associated with a specific adrenal adenoma mutation.\"}]","Interpretable Machine Learning in Endocrinology - A Diagnostic Tool in Primary Aldosteronism | PDF",1785733707,28,{"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":86,"head_meta":88,"extra_data":90,"updated_unix":28},"interpretable-machine-learning-in-endocrinology-a-diagnostic-tool-in-primary-aldosteronism","",{"@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/interpretable-machine-learning-in-endocrinology-a-diagnostic-tool-in-primary-aldosteronism/121097/",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","2026-08-03",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 data type does the approach use for diagnosing Primary Aldosteronism?","Question",{"text":75,"@type":76},"It uses urinary steroid metabolomics (USM), analyzing steroid metabolite excretion profiles in urine to support diagnosis.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which machine learning method is highlighted in this contribution?",{"text":80,"@type":76},"The results focus on a prototype-based Generalized Matrix Relevance Learning Vector Quantization (GMLR-LVQ) model for classification of metabolomics profiles.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the method contribute beyond classification?",{"text":84,"@type":76},"It provides insights into the importance of available markers and enables non-invasive identification of a subtype of Primary Aldosteronism associated with a specific adrenal adenoma mutation.","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},[93,97,101,105,110,115,120,123,128,131,135],{"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":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":46,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":46,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":46,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":46,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]