MEDOBO: 18 Million+ MEDLINE Abstracts Tagged with OBO Ontologies

MEDOBO: 18 Million+ MEDLINE Abstracts Tagged with OBO Ontologies | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article MEDOBO: 18 Million+ MEDLINE Abstracts Tagged with OBO Ontologies Ahmad Aghaebrahimian, Maria Anisimova, Manuel Gil This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2772648/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Motivation: The number of biomedical and life science publications is rapidly increasing, with MEDLINE alone having over 30 million citations. The massive amount of information highlights the need for biomedical text analytics to improve the accessibility of bio-data. However, the presence of multiple subdomains within life sciences poses a significant challenge. To address this, an automatic classification system is required that can annotate texts with relevant subdomains in a text analytics pipeline. This will make text processing more efficient and precise for subsequent modules in the pipeline by reducing their search space to concepts within a limited set of subdomains. The development of text classification systems for life sciences subdomains requires training data as the first requirement, but unfortunately, a high-quality and large-scale dataset for this task is lacking. Results: We present MEDOBO, a dataset comprising over 18 million MEDLINE abstracts that have been automatically labeled with ontologies from the Open Biological and Biomedical Ontology (OBO) Foundry using Medical Subject Headings (MeSH). Our dataset has achieved a conformity score of over 91% F1 when compared to an expert-annotated dataset. We have trained multiple models on MEDOBO to evaluate distribution and classification difficulty and the results indicate significant potential for enhancing multi-label text classification. Bioinformatics Artificial Intelligence and Machine Learning Semantic Annotation Biomedical Text Classification Ontology Indexing Biomedical Ontology Assignment UMLS MeSH Full Text Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2772648","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":188815585,"identity":"f4fce48a-83fc-4f4b-b462-00a6ceaa31c1","order_by":0,"name":"Ahmad Aghaebrahimian","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAApUlEQVRIiWNgGAWjYFACHgaGDwwHQCw24rUwziBZCzMPSVr4+9ce/Gzz5468wQHmZw+I0iJx412ydA7PM8MNB9jMDYiz5sYZA+kcicOM2w7wsEkQpUP+xhnj3xYGh+2J12JwvsdMmiHhcCLxWgxv8JhZ9hw4nLz/MJsZcVrkzp8xvvHjz2Hbme3Nz4jTwiCRAGUwE6ceCPgPEK10FIyCUTAKRioAAPlzMQOm79fJAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0003-0480-2505","institution":"Institute of Computational Life Sciences","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Ahmad","middleName":"","lastName":"Aghaebrahimian","suffix":""},{"id":188815586,"identity":"e03a12c1-b582-4c90-b0e1-627ecf687a8d","order_by":1,"name":"Maria Anisimova","email":"","orcid":"","institution":"Institute of Computational Life Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maria","middleName":"","lastName":"Anisimova","suffix":""},{"id":188815587,"identity":"a309638b-88dc-4bb1-bf3b-9c482d161990","order_by":2,"name":"Manuel Gil","email":"","orcid":"","institution":"Institute of Computational Life Sciences","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Manuel","middleName":"","lastName":"Gil","suffix":""}],"badges":[],"createdAt":"2023-04-03 15:52:32","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false,"coiExplicitlySet":false},"doi":"10.21203/rs.3.rs-2772648/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2772648/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":35242675,"identity":"dda23c2f-1161-4184-866c-d689521befe8","added_by":"auto","created_at":"2023-04-04 04:55:10","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":444396,"visible":true,"origin":"","legend":"","description":"","filename":"MEDOBOBMCsubmitted.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2772648/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eMEDOBO: 18 Million+ MEDLINE Abstracts Tagged with OBO Ontologies\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Institute of Computational Life Sciences","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Semantic Annotation, Biomedical Text Classification, Ontology Indexing, Biomedical Ontology Assignment, UMLS, MeSH","lastPublishedDoi":"10.21203/rs.3.rs-2772648/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2772648/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eMotivation: \u003c/strong\u003eThe number of biomedical and life science publications is rapidly increasing, with MEDLINE alone having over 30 million citations. 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