[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-126996-en":3,"doc-seo-126996-105":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},126996,687207024643,"Oliver","https://ap-avatar.wpscdn.com/davatar_3d24733baf745e90a7e4bdd5f77d97b2",8,"Research & Report","Machine learning for catalysing the integration of noncoding RNA in research and clinical practice","The human transcriptome is largely composed of noncoding RNAs (ncRNAs), which regulate many disease-relevant pathophysiological processes and provide a valuable source of next-generation biomarkers. Integrating ncRNA transcripts with clinical records and multi-omics data has driven the adoption of artificial intelligence and machine learning methods. Due to biological complexity, ML is becoming central to ncRNA research, including the discovery of clinically relevant biomarkers and elucidation of ncRNA-associated pathogenetic mechanisms. The article reviews key opportunities and challenges, addresses methodological and conceptual constraints, and discusses ethical considerations for AI in healthcare and research.","Roskilde University  \nMachine learning for catalysing the integration of noncoding RNA in research and clinical practice  \nde Gonzalo-Calvo, David; Karaduzovic-Hadziabdic, Kanita; Dalgaard, Louise Torp; Dieterich, Christoph; Perez-Pons, Manel; Hatzigeorgiou, Artemis; Devaux, Yvan; Kararigas, Georgios Published in:  \neBioMedicine  \nDOI:  \n10.1016/j.ebiom.2024.105247  \nPublication date:  \n2024  \nDocument Version  \nPublisher's PDF, also known as Version of record  \nCitation for published version (APA):  \nde Gonzalo-Calvo, D. , Karaduzovic-Hadziabdic, K. , Dalgaard, L. T. , Dieterich, C. , Perez-Pons, M. , Hatzigeorgiou, A. , Devaux, Y. , & Kararigas, G. (2024) . Machine learning for catalysing the integration of noncoding RNA in research and clinical practice. eBioMedicine , 106, Article 105247.  \n[https://doi.org/10.1016/j.ebiom.2024.105247](https://doi.org/10.1016/j.ebiom.2024.105247)  \nGeneral rights  \nCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.  \n• Users may download and print one copy of any publication from the public 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 public portal.  \nTake down policy  \nIf you believe that this document breaches copyright please contact [rucforsk@kb.dk](rucforsk@kb.dk) providing details, and we will remove access to the work immediately and investigate your claim.  \nDownload date: 10. Jan. 2025  \nReview   \nMachine learning for catalysing the integration of noncoding RNA in research and clinical practice  \nDavid de Gonzalo-Calvo,a,b,∗ Kanita Karaduzovic-Hadziabdic,c Louise Torp Dalgaard,d Christoph Dieterich,e,f Manel Perez-Pons,a,b Artemis Hatzigeorgiou,g,h Yvan Devaux,i and Georgios Kararigasj,∗∗  \naTranslational Research in Respiratory Medicine, University Hospital Arnau de Vilanova and Santa Maria, IRBLleida, Lleida, Spain bCIBER of Respiratory Diseases (CIBERES), Institute of Health Carlos III, Madrid, Spain  \ncFaculty of Engineering and Natural Sciences, International University of Sarajevo, Sarajevo, Bosnia and Herzegovina dDepartment of Science and Environment, Roskilde University, Roskilde, Denmark  \neKlaus Tschira Institute for Integrative Computational Cardiology and Department of Internal Medicine III, University Hospital Heidelberg, Germany  \nfGerman Center for Cardiovascular Research (DZHK) - Partner Site Heidelberg/Mannheim, Germany  \ngDIANA-Lab, Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece hHellenic Pasteur Institute, Athens, Greece  \niCardiovascular Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg jDepartment of Physiology, Faculty of Medicine, University of Iceland, Reykjavik, Iceland  \nSummary  \nThe human transcriptome predominantly consists of noncoding RNAs (ncRNAs), transcripts that do not encode proteins. The noncoding transcriptome governs a multitude of pathophysiological processes, offering a rich source of next-generation biomarkers. Toward achieving a holistic view of disease, the integration of these transcripts with clinical records and additional data from omic technologies (“multiomic” strategies) has motivated the adoption of artificial intelligence (AI) approaches. Given their intricate biological complexity, machine learning (ML) techniques are becoming a key component of ncRNA-based research. This article presents an overview of the potential and challenges associated with employing AI/ML-driven approaches to identify clinically relevant ncRNA biomarkers and to decipher ncRNA-associated pathogenetic mechanisms. Methodological and conceptual const","cbCaieodcr83Tio9","https://ap.wps.com/l/cbCaieodcr83Tio9","pdf",703987,1,17,"English","en",105,"# Summary\n## Background and rationale\n## Methods and key focus\n## Challenges and constraints\n## Ethical considerations\n## Clinical implications","[{\"question\":\"What ethical considerations are highlighted for AI applications in healthcare and research?\",\"answer\":\"The article discusses ethical considerations inherent to AI applications in both healthcare and research contexts, alongside other constraints, to support responsible deployment of these tools.\"}]","Machine learning for catalysing the integration of noncoding RNA in research and clinical practice | PDF",1785936111,43,{"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},"machine-learning-for-catalysing-the-integration-of-noncoding-rna-in-research-and-clinical-practice","",{"@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/machine-learning-for-catalysing-the-integration-of-noncoding-rna-in-research-and-clinical-practice/126996/",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","2026-08-22","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 ethical considerations are highlighted for AI applications in healthcare and research?","Question",{"text":76,"@type":77},"The article discusses ethical considerations inherent to AI applications in both healthcare and research contexts, alongside other constraints, to support responsible deployment of these tools.","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},[86,90,94,98,103,108,113,116,121,124,128],{"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":125,"doc_module":4,"doc_module_name":46,"category_name":126,"show_sort_weight":125,"slug":127},10,"Lifestyle","lifestyle",{"id":129,"doc_module":4,"doc_module_name":46,"category_name":130,"show_sort_weight":99,"slug":131},19,"General","general"]