{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T09:49:03Z","timestamp":1747216143406,"version":"3.40.5"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"type":"print","value":"9781643684000"},{"type":"electronic","value":"9781643684017"}],"license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,29]]},"abstract":"<jats:p>Currently, there is very little research aimed at developing medical knowledge extraction tools for major West Slavic languages (Czech, Polish, and Slovak). This project lays the groundwork for a general medical knowledge extraction pipeline, introducing the resource vocabularies available for the respective languages (UMLS resources, ICD-10 translations and national drug databases). It demonstrates the utility of this approach on a case study using a large proprietary corpus of Czech oncology records consisting of more than 40 million words written about more than 4,000 patients. After correlating MedDRA terms found in patients\u2019 records with drugs prescribed to them, significant non-obvious associations were found between selected medical conditions being mentioned and the probability of certain drugs being prescribed over the course of the patient\u2019s treatment, in some cases increasing the probability of prescriptions by over 250%. This direction of research, producing large amounts of annotated data, is a prerequisite for training deep learning models and predictive systems.<\/jats:p>","DOI":"10.3233\/shti230433","type":"book-chapter","created":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T07:52:11Z","timestamp":1688111531000},"source":"Crossref","is-referenced-by-count":0,"title":["Understanding Health Records in West Slavic Languages: Available Resources, Case Study in Oncology"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5237-9735","authenticated-orcid":false,"given":"Kristof","family":"Anetta","sequence":"first","affiliation":[{"name":"NLP Centre, Faculty of Informatics, Masaryk University Brno, Czech Republic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","Healthcare Transformation with Informatics and Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI230433","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,30]],"date-time":"2023-06-30T07:52:12Z","timestamp":1688111532000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI230433"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,29]]},"ISBN":["9781643684000","9781643684017"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti230433","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"type":"print","value":"0926-9630"},{"type":"electronic","value":"1879-8365"}],"subject":[],"published":{"date-parts":[[2023,6,29]]}}}