BURŠA, M., L. LHOTSKÁ, V. CHUDÁČEK, J. SPILKA, Petr JANKŮ and Martin HUSER. Practical problems and solutions in hospital information system data mining. In Christian Böhm, Sami Khuri, Lenka Lhotská, M. Elena Renda. Information Technology in Bio- and Medical Informatics, Third International Conference, ITBAM 2012. Vídeň: Springer Berlin Heidelberg, 2012, p. 31-39. ISBN 978-3-642-32394-2. Available from: https://dx.doi.org/10.1007/978-3-642-32395-9_3.
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Basic information
Original name Practical problems and solutions in hospital information system data mining
Authors BURŠA, M. (203 Czech Republic, guarantor), L. LHOTSKÁ (203 Czech Republic), V. CHUDÁČEK (203 Czech Republic), J. SPILKA (203 Czech Republic), Petr JANKŮ (203 Czech Republic, belonging to the institution) and Martin HUSER (203 Czech Republic, belonging to the institution).
Edition Vídeň, Information Technology in Bio- and Medical Informatics, Third International Conference, ITBAM 2012, p. 31-39, 9 pp. 2012.
Publisher Springer Berlin Heidelberg
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20206 Computer hardware and architecture
Country of publisher Austria
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14110/12:00064000
Organization unit Faculty of Medicine
ISBN 978-3-642-32394-2
Doi http://dx.doi.org/10.1007/978-3-642-32395-9_3
Keywords in English Swarm Intelligence; Ant Colony; Text Data Mining; Information Retrieval; Hospital Information System
Changed by Changed by: Ing. Mgr. Věra Pospíšilíková, učo 9005. Changed: 25/2/2013 05:38.
Abstract
Information mining from textual data becomes a very challenging task when the structure of the text record is very loose without any rules. Doctors often use natural language in medical records. Therefore it contains many ambiguities due to non-standard abbreviations and synonyms. The medical environment itself is also very specific: the natural language used in textual description varies with the personality creating the record (there are many personalized approaches), however it is restricted by terminology (i.e. medical terms, medical standards, etc.). Moreover, the typical patient record is filled with typographical errors, duplicates, ambiguities, syntax errors and many nonstandard abbreviations.
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