Practical problems and solutions in hospital information system
data mining

D 2012

Practical problems and solutions in hospital information system data mining

BURŠA, M., L. LHOTSKÁ, V. CHUDÁČEK, J. SPILKA, Petr JANKŮ et. al.

Základní údaje

Originální název

Practical problems and solutions in hospital information system data mining

Autoři

BURŠA, M. (203 Česká republika, garant), L. LHOTSKÁ (203 Česká republika), V. CHUDÁČEK (203 Česká republika), J. SPILKA (203 Česká republika), Petr JANKŮ (203 Česká republika, domácí) a Martin HUSER (203 Česká republika, domácí)

Vydání

Vídeň, Information Technology in Bio- and Medical Informatics, Third International Conference, ITBAM 2012, od s. 31-39, 9 s. 2012

Nakladatel

Springer Berlin Heidelberg

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

20206 Computer hardware and architecture

Stát vydavatele

Rakousko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Kód RIV

RIV/00216224:14110/12:00064000

Organizační jednotka

Lékařská fakulta

ISBN

978-3-642-32394-2

DOI

http://dx.doi.org/10.1007/978-3-642-32395-9_3

Klíčová slova anglicky

Swarm Intelligence; Ant Colony; Text Data Mining; Information Retrieval; Hospital Information System

Změněno: 25. 2. 2013 05:38, Ing. Mgr. Věra Pospíšilíková

Anotace

V originále

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.

Citovat

BURŠA, M., L. LHOTSKÁ, V. CHUDÁČEK, J. SPILKA, Petr JANKŮ a 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, s. 31-39. ISBN 978-3-642-32394-2. Dostupné z: https://dx.doi.org/10.1007/978-3-642-32395-9_3.

@inproceedings{1088414,
   author = {Burša, M. and Lhotská, L. and Chudáček, V. and Spilka, J. and Janků, Petr and Huser, Martin},
   address = {Vídeň},
   booktitle = {Information Technology in Bio- and Medical Informatics, Third International Conference, ITBAM 2012},
   doi = {http://dx.doi.org/10.1007/978-3-642-32395-9_3},
   editor = {Christian Böhm, Sami Khuri, Lenka Lhotská, M. Elena Renda},
   keywords = {Swarm Intelligence; Ant Colony; Text Data Mining; Information Retrieval; Hospital Information System},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Vídeň},
   isbn = {978-3-642-32394-2},
   pages = {31-39},
   publisher = {Springer Berlin Heidelberg},
   title = {Practical problems and solutions in hospital information system data mining},
   year = {2012}
}

TY  - JOUR
ID  - 1088414
AU  - Burša, M. - Lhotská, L. - Chudáček, V. - Spilka, J. - Janků, Petr - Huser, Martin
PY  - 2012
TI  - Practical problems and solutions in hospital information system data mining
PB  - Springer Berlin Heidelberg
CY  - Vídeň
SN  - 9783642323942
KW  - Swarm Intelligence
KW  - Ant Colony
KW  - Text Data Mining
KW  - Information Retrieval
KW  - Hospital Information System
N2  - 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.
ER  -

BURŠA, M., L. LHOTSKÁ, V. CHUDÁČEK, J. SPILKA, Petr JANKŮ a Martin HUSER. Practical problems and solutions in hospital information system data mining. In Christian Böhm, Sami Khuri, Lenka Lhotská, M. Elena Renda. \textit{Information Technology in Bio- and Medical Informatics, Third International Conference, ITBAM 2012}. Vídeň: Springer Berlin Heidelberg, 2012, s.~31-39. ISBN~978-3-642-32394-2. Dostupné z: https://dx.doi.org/10.1007/978-3-642-32395-9\_{}3.

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