{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:20:20Z","timestamp":1740201620993,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"abstract":"<jats:p>In this paper we present a framework for the semi-automatic extraction of medical entities from referral letters and use them to transcribe a case report form. Our framework offers the functionality to: (a) extract the medical entity from the unstructured referral letters, (b) classify them according to their semantic type, and (c) transcribe a case report form based on the extracted information from the referral letter. We take a semantic text analytics approach where SNOMED-CT ontology is used to both classify referral concepts and to establish semantic similarities between referral concepts and CRF elements. We used 100 spine injury referral letters, and a standard case report form used by Association of Dalhousie Neurosurgeons, Dalhousie University.<\/jats:p>","DOI":"10.3233\/978-1-61499-678-1-322","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:07:16Z","timestamp":1740121636000},"source":"Crossref","is-referenced-by-count":0,"title":["Transcription of Case Report Forms from Unstructured Referral Letters: A Semantic Text Analytics Approach"],"prefix":"10.3233","author":[{"family":"Abidi Syed Sibte Raza","sequence":"additional","affiliation":[]},{"family":"Singh Abhinav Kumar","sequence":"additional","affiliation":[]},{"family":"Christie Sean","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Exploring Complexity in Health: An Interdisciplinary Systems Approach"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:44:11Z","timestamp":1740123851000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-677-4&spage=322&doi=10.3233\/978-1-61499-678-1-322"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-678-1-322","relation":{},"ISSN":["0926-9630"],"issn-type":[{"value":"0926-9630","type":"print"}],"subject":[],"published":{"date-parts":[[2016]]}}}