Dimitar Tcharaktchiev

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FOREWORD This volum e contains the pap ers accepted at the 2nd w orkshop on Building and Evaluating Resources for Biomedical Text Mining held at LREC 2010, Malta. Biomedical text mining over the last decade has become one of the d riving application areas for the NLP community, resulting in a series of very successful yearly specialist wo rkshops at ACL(More)
The presented paper discusses a hybrid approach for negation processing in Electronic Health Records (EHRs) in Bulgarian. The rich temporal structure and the specific combination of medical terminology in both Bulgarian and Latin do not allow the application of standard language processing techniques. The problem gets even worse due to the often use of(More)
Information Extraction (IE) from medical texts aims at the automatic recognition of entities and relations of interests. IE is based on shallow analysis and considers only sentences containing important words. Thus IE of drugs from discharge letters can identify as 'current' some past or future medication events. This article presents heuristic observations(More)
The paper discusses an Information Extraction approach, which is applied for the automatic processing of hospital Patient Records (PRs) in Bulgarian language. The main task reported here is retrieval of status descriptions related to anatomical organs. Due to the specific telegraphic PR style, the approach is focused on shallow analysis. Missing text(More)
This article describes the automatic processing of medical texts in order to extract important patient characteristics, thus turning the free text description into a structured internal representation. Shallow text analysis is implemented due to the medical language complexity. The paper sketches the information extraction process and discusses the role of(More)