BERKA, Petr, J. JABLONSKÝ, Luboš MAREK and Michal VRABEC. Analysis of Neurosurgery Data Using Statistical and Data Mining Methods. In Lagunas, OP; Alcantara, OH; Figueroa, GA. Advances in Artificial Intelligence and Its Applications. 14th. Mexican Int. Conference on Artificial Intelligence. 9414th ed. Switzerland: Springer International Publishing, 2015, p. 310-321. ISBN 978-3-319-27100-2. Available from: https://dx.doi.org/10.1007/978-3-319-27101-9_23.
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Basic information
Original name Analysis of Neurosurgery Data Using Statistical and Data Mining Methods
Authors BERKA, Petr (203 Czech Republic, guarantor, belonging to the institution), J. JABLONSKÝ (203 Czech Republic), Luboš MAREK (203 Czech Republic) and Michal VRABEC (203 Czech Republic).
Edition 9414. vyd. Switzerland, Advances in Artificial Intelligence and Its Applications. 14th. Mexican Int. Conference on Artificial Intelligence, p. 310-321, 12 pp. 2015.
Publisher Springer International Publishing
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Switzerland
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/04274644:_____/15:#0000087
Organization unit University of Finance and Administration
ISBN 978-3-319-27100-2
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-319-27101-9_23
UT WoS 000367681400023
Keywords in English Engineering controlled terms; Artificial intelligence; Decision trees; Neurosurgery; Patient monitoring; Patient treatment; Surgery; Trees (mathematics)
Tags AR 2015-2016, D2, RIV_ne, SCOPUS, WOS, xD1
Tags International impact, Reviewed
Changed by Changed by: Ing. Dominika Moravcová, učo 21787. Changed: 29/3/2017 14:52.
Abstract
The data concerning the outcomes of surgical clipping and endovascular treatment in acute aneurysmal subarachnoid hemorrhage (SAH) patients have been analyzed to reveal relations between subjective neuropsychological assessments, measurable characteristics of the patient and the disease, and the type of treatment the patient had undergone one year before. We build upon results of previous analyses where have been found that the differences in neuropsychological assessment of the patients treated by either coiling or clipping was small and slightly in favor of surgical group. Using this data, we compare the “classical” statistical and data mining approach. While statistics offers techniques based on contingency tables, where the compared variables have to be manually selected, data mining methods like association rules, decision rules or decision trees offer the possibility to generate and evaluate a number of more complex hypotheses about the hidden relationships. We used SAS JMP to perform the statistical analysis and LISp-Miner system for the data mining experiments. © Springer International Publishing Switzerland 2015.
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