Information retrieval from hospital information system:
Increasing effectivity using swarm intelligence

J 2015

Information retrieval from hospital information system: Increasing effectivity using swarm intelligence

BURSA, Miroslav, Lenka LHOTSKA, Vaclav CHUDACEK, Jiri SPILKA, Petr JANKŮ et. al.

Základní údaje

Originální název

Information retrieval from hospital information system: Increasing effectivity using swarm intelligence

Autoři

BURSA, Miroslav (203 Česká republika), Lenka LHOTSKA (203 Česká republika), Vaclav CHUDACEK (203 Česká republika), Jiri SPILKA (203 Česká republika), Petr JANKŮ (203 Česká republika, garant, domácí) a Lukáš HRUBAN (203 Česká republika, domácí)

Vydání

Journal of Applied Logic, Amsterdam, ELSEVIER SCIENCE BV, 2015, 1570-8683

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30214 Obstetrics and gynaecology

Stát vydavatele

Nizozemské království

Utajení

není předmětem státního či obchodního tajemství

Impakt faktor

Impact factor: 0.524

Kód RIV

RIV/00216224:14110/15:00082475

Organizační jednotka

Lékařská fakulta

DOI

http://dx.doi.org/10.1016/j.jal.2014.11.006

UT WoS

000350924200005

Klíčová slova anglicky

Swarm intelligence; Ant colony; Textual data mining; Medical record processing; Hospital information system

Štítky

EL OK

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 14. 4. 2015 09:22, Ing. Mgr. Věra Pospíšilíková

Anotace

V originále

This paper details the process of mining information from a hospital information system that has been designed approximately 15years ago. The information is distributed within database tables in largetextual attributes with a free structure. Information retrieval from these information is necessary for complementing cardiotocography signals with additional information that isto be implemented in a decision support system. The basic statistical overview (n-gram analysis) helped with the insight into data structure, however more sophisticated methods have to be used as human (and expert) processing of the whole data wereout of consideration: over 620,000text fields containedtext reports in natural language with (many) typographical errors, duplicates, ambiguities, syntax errors and many (nonstandard) abbreviations. There was a strong need to efficiently determine the overall structure of the database and discover information that isimportant from the clinical point of view. We have used three different methods: k-means, self-organizing map and a self-organizing approach inspired by ant-colonies that performed clustering of the records. The records were visualized and revealed the most prominent information structure(s) that were consulted with medical experts and served for further mining from the database. The outcome of this task is a set of ordered or nominal attributes with a structural information that is available for rule discovery mining and automated processing for the research of asphyxia prediction during delivery. The proposed methodology has significantly reduced the processing time of loosely structured textual records for both IT and medical experts.

Citovat

BURSA, Miroslav, Lenka LHOTSKA, Vaclav CHUDACEK, Jiri SPILKA, Petr JANKŮ a Lukáš HRUBAN. Information retrieval from hospital information system: Increasing effectivity using swarm intelligence. Journal of Applied Logic. Amsterdam: ELSEVIER SCIENCE BV, 2015, roč. 13, č. 2, s. 126-137. ISSN 1570-8683. Dostupné z: https://dx.doi.org/10.1016/j.jal.2014.11.006.

@article{1229187,
   author = {Bursa, Miroslav and Lhotska, Lenka and Chudacek, Vaclav and Spilka, Jiri and Janků, Petr and Hruban, Lukáš},
   article_location = {Amsterdam},
   article_number = {2},
   doi = {http://dx.doi.org/10.1016/j.jal.2014.11.006},
   keywords = {Swarm intelligence; Ant colony; Textual data mining; Medical record processing; Hospital information system},
   language = {eng},
   issn = {1570-8683},
   journal = {Journal of Applied Logic},
   title = {Information retrieval from hospital information system: Increasing effectivity using swarm intelligence},
   volume = {13},
   year = {2015}
}

TY  - JOUR
ID  - 1229187
AU  - Bursa, Miroslav - Lhotska, Lenka - Chudacek, Vaclav - Spilka, Jiri - Janků, Petr - Hruban, Lukáš
PY  - 2015
TI  - Information retrieval from hospital information system: Increasing effectivity using swarm intelligence
JF  - Journal of Applied Logic
VL  - 13
IS  - 2
SP  - 126-137
EP  - 126-137
PB  - ELSEVIER SCIENCE BV
SN  - 15708683
KW  - Swarm intelligence
KW  - Ant colony
KW  - Textual data mining
KW  - Medical record processing
KW  - Hospital information system
N2  - This paper details the process of mining information from a hospital information system that has been designed approximately 15years ago. The information is distributed within database tables in largetextual attributes with a free structure. Information retrieval from these information is necessary for complementing cardiotocography signals with additional information that isto be implemented in a decision support system. The basic statistical overview (n-gram analysis) helped with the insight into data structure, however more sophisticated methods have to be used as human (and expert) processing of the whole data wereout of consideration: over 620,000text fields containedtext reports in natural language with (many) typographical errors, duplicates, ambiguities, syntax errors and many (nonstandard) abbreviations. There was a strong need to efficiently determine the overall structure of the database and discover information that isimportant from the clinical point of view. We have used three different methods: k-means, self-organizing map and a self-organizing approach inspired by ant-colonies that performed clustering of the records. The records were visualized and revealed the most prominent information structure(s) that were consulted with medical experts and served for further mining from the database. The outcome of this task is a set of ordered or nominal attributes with a structural information that is available for rule discovery mining and automated processing for the research of asphyxia prediction during delivery. The proposed methodology has significantly reduced the processing time of loosely structured textual records for both IT and medical experts.
ER  -

BURSA, Miroslav, Lenka LHOTSKA, Vaclav CHUDACEK, Jiri SPILKA, Petr JANKŮ a Lukáš HRUBAN. Information retrieval from hospital information system: Increasing effectivity using swarm intelligence. \textit{Journal of Applied Logic}. Amsterdam: ELSEVIER SCIENCE BV, 2015, roč.~13, č.~2, s.~126-137. ISSN~1570-8683. Dostupné z: https://dx.doi.org/10.1016/j.jal.2014.11.006.

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