{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,23]],"date-time":"2025-02-23T00:10:31Z","timestamp":1740269431473,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"abstract":"<jats:p>Relation extraction typically involves the extraction of relations between two or more entities occurring within a single or multiple sentences. In this study, we investigated the significance of extracting information from multiple sentences specifically in the context of drug-disease relation discovery. We used multiple resources such as Semantic Medline, a literature based resource, and Medline search (for filtering spurious results) and inferred 8,772 potential drug-disease pairs. Our analysis revealed that 6,450 (73.5%) of the 8,772 potential drug-disease relations did not occur in a single sentence. Moreover, only 537 of the drug-disease pairs matched the curated gold standard in Comparative Toxicogenomics Database (CTD), a trusted resource for drug-disease relations. Among the 537, nearly 75% (407) of the drug-disease pairs occur in multiple sentences. Our analysis revealed that the drug-disease pairs inferred from Semantic Medline or retrieved from CTD could be extracted from multiple sentences in the literature. This highlights the significance of the need of discourse-level analysis in extracting the relations from biomedical literature.<\/jats:p>","DOI":"10.3233\/978-1-61499-564-7-539","type":"book-chapter","created":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T23:19:12Z","timestamp":1740266352000},"source":"Crossref","is-referenced-by-count":0,"title":["Assessing the Need of Discourse-Level Analysis in Identifying Evidence of Drug-Disease Relations in Scientific Literature"],"prefix":"10.3233","author":[{"family":"Rastegar-Mojarad Majid","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Komandur Elayavilli Ravikumar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Li Dingcheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Liu Hongfang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2015: eHealth-enabled Health"],"original-title":[],"deposited":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T23:29:01Z","timestamp":1740266941000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-563-0&spage=539&doi=10.3233\/978-1-61499-564-7-539"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-564-7-539","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2015]]}}}