The power of graphs in medicine: Introducing BioGraphSum for effective text summarization

Basit Öğe Kaydı
dc.contributor.authorHark, Cengiz
dc.date.accessioned2024-08-04T20:56:03Z
dc.date.available2024-08-04T20:56:03Z
dc.date.issued2024
dc.departmentİnönü Üniversitesien_US
dc.description.abstractIn biomedicine, the expansive scientific literature combined with the frequent use of abbreviations, acronyms, and symbols presents considerable challenges for text processing and summarization. The Unified Medical Language System (UMLS) has been a go-to for extracting concepts and determining correlations in these studies; hence, the BioGraphSum model introduced in this study aims to reduce this UMLS dependence. Through adoption of an innovative perspective, sentences within a piece of text are graphically conceptualized as nodes, enabling the concept of Malatya centrality to be leveraged. This approach focuses on pinpointing influential nodes on a graph and, by analogy, the most pertinent sentences within the text for summarization. In order to evaluate the performance of the BioGraphSum approach, a corpus was curated that consisted of 450 contemporary scientific research articles available on the PubMed database, aligned with proven research methodology. The BioGraphSum model was subjected to rigorous testing against this corpus in order to demonstrate its capabilities. Preliminary results, especially in the precision-based and f-score-based ROUGE-(1-2), ROUGE-L, and ROUGE-SU metrics reported significant improvements when compared to other existing models considered state-of-the-art in text summarization.en_US
dc.identifier.doi10.1016/j.heliyon.2024.e31813
dc.identifier.issn2405-8440
dc.identifier.issue11en_US
dc.identifier.pmid38845961en_US
dc.identifier.scopus2-s2.0-85194134819en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.heliyon.2024.e31813
dc.identifier.urihttps://hdl.handle.net/11616/102013
dc.identifier.volume10en_US
dc.identifier.wosWOS:001246681800002en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakPubMeden_US
dc.language.isoenen_US
dc.publisherCell Pressen_US
dc.relation.ispartofHeliyonen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDocument summarizationen_US
dc.subjectMulti -document summarizationen_US
dc.subjectMinimum vertex coveren_US
dc.subjectROUGEen_US
dc.titleThe power of graphs in medicine: Introducing BioGraphSum for effective text summarizationen_US
dc.typeArticleen_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
PubMed İndeksli Yayın Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu