Cross-Learning on Multiple Databases in the Case of Acute Appendicitis

CC
CBMS
2001
14th IEEE Symposium on Computer-Based Medical Systems (CMBS'01)
Abstract - Cross-Learning on Multiple Databases in the Case of Acute Appendicitis

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	Similar Articles Articles by V. Podgorelec Articles by M. Zorman Articles by P. Kokol Articles by H.-P. Eich Articles by C. Ohmann

14th IEEE Symposium on Computer-Based Medical Systems (CMBS'01)

Bethesda, Maryland

March 26-March 27

ISBN: 0-7695-1004-3

	ASCII Text	x
	V. Podgorelec, M. Zorman, P. Kokol, H.-P. Eich, C. Ohmann, "Cross-Learning on Multiple Databases in the Case of Acute Appendicitis," Computer-Based Medical Systems, IEEE Symposium on, pp. 0017, 14th IEEE Symposium on Computer-Based Medical Systems (CMBS'01), 2001.

	BibTex	x
	@article{ 10.1109/CBMS.2001.941691, author = {V. Podgorelec and M. Zorman and P. Kokol and H.-P. Eich and C. Ohmann}, title = {Cross-Learning on Multiple Databases in the Case of Acute Appendicitis}, journal ={Computer-Based Medical Systems, IEEE Symposium on}, volume = {0}, year = {2001}, isbn = {0-7695-1004-3}, pages = {0017}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2001.941691}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer-Based Medical Systems, IEEE Symposium on TI - Cross-Learning on Multiple Databases in the Case of Acute Appendicitis SN - 0-7695-1004-3 SP EP A1 - V. Podgorelec, A1 - M. Zorman, A1 - P. Kokol, A1 - H.-P. Eich, A1 - C. Ohmann, PY - 2001 VL - 0 JA - Computer-Based Medical Systems, IEEE Symposium on ER -

V. Podgorelec, University of Maribor

M. Zorman, University of Maribor

P. Kokol, University of Maribor

H.-P. Eich, Heinrich-Heine University D?sseldorf

C. Ohmann, Heinrich-Heine University D?sseldorf

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2001.941691

Abstract: We study the cross-learning approach on multiple databases to predict the acute appendicitis. For the machine learning algorithm our evolutionary method for inducing decision trees is used. The results of cross-learning are presented for the three different databases obtained in the international projects regarding the acute abdominal pain.

Citation:

V. Podgorelec, M. Zorman, P. Kokol, H.-P. Eich, C. Ohmann, "Cross-Learning on Multiple Databases in the Case of Acute Appendicitis," cbms, pp.0017, 14th IEEE Symposium on Computer-Based Medical Systems (CMBS'01), 2001

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