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2017 | OriginalPaper | Chapter

Logistic Regression Methods in Selected Medical Information Systems

Authors : Anna Kasperczuk, Agnieszka Dardzinska

Published in: Future Data and Security Engineering

Publisher: Springer International Publishing

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Abstract

This paper presents the process of building a new logistic regression model, which aims to support the decision-making process in medical database. The developed logistic regression model defines the probability of the disease and indicates the statistically significant changes that affect the onset of the disease. The value of probability can be treated as one of the feature in decision process of patient’s future treatment.

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Literature
1.
go back to reference Bender, R., Grouven, U.: Logistic regression models used in medical research are poorly presented [Letter]. BMJ 313, 628 (1996)CrossRef Bender, R., Grouven, U.: Logistic regression models used in medical research are poorly presented [Letter]. BMJ 313, 628 (1996)CrossRef
2.
go back to reference Campillo, C.: Standardizing criteria for logistic regression models. Ann. Intern. Med. 119, 540–541 (1993)CrossRef Campillo, C.: Standardizing criteria for logistic regression models. Ann. Intern. Med. 119, 540–541 (1993)CrossRef
3.
go back to reference Chin, S.: The rise and fall of logistic regression. Aust. Epidemiol. 8, 7–10 (2001) Chin, S.: The rise and fall of logistic regression. Aust. Epidemiol. 8, 7–10 (2001)
5.
go back to reference Hall, G.H., Round, A.P.: Logistic regression: explanation and use. J. R. Coll. Physicians Lond. 28, 242–246 (1994) Hall, G.H., Round, A.P.: Logistic regression: explanation and use. J. R. Coll. Physicians Lond. 28, 242–246 (1994)
6.
8.
go back to reference Jiang, H., Kulkarni, P.M., Mallinckrodt, C.H., Shurzinske, L., Molenberghs, G., Lipkovich, I.: To adjust or not to adjust for baseline when analyzing repeated binary responses? The case of complete data when treatment comparison at study end is of interest. Pharm. Stat. 14, 262–271 (2015)CrossRef Jiang, H., Kulkarni, P.M., Mallinckrodt, C.H., Shurzinske, L., Molenberghs, G., Lipkovich, I.: To adjust or not to adjust for baseline when analyzing repeated binary responses? The case of complete data when treatment comparison at study end is of interest. Pharm. Stat. 14, 262–271 (2015)CrossRef
9.
go back to reference de Jong, P., Heller, G.Z.: Generalized Linear Models for Insurance Data. Cambridge University Press, Cambridge (2008)CrossRefMATH de Jong, P., Heller, G.Z.: Generalized Linear Models for Insurance Data. Cambridge University Press, Cambridge (2008)CrossRefMATH
10.
go back to reference Kasperczuk, A., Dardzinska, A.: Comparative evaluation of the different data mining techniques used for the medical database. Acta Mechanica et Automatica 10(3), 233–238 (2016)CrossRef Kasperczuk, A., Dardzinska, A.: Comparative evaluation of the different data mining techniques used for the medical database. Acta Mechanica et Automatica 10(3), 233–238 (2016)CrossRef
11.
go back to reference Khan, K.S., Chien, P.F., Dwarakanath, L.S.: Logistic regression models in obstetrics and gynecology literature. Obstet. Gynecol. 93, 10014–10020 (1999) Khan, K.S., Chien, P.F., Dwarakanath, L.S.: Logistic regression models in obstetrics and gynecology literature. Obstet. Gynecol. 93, 10014–10020 (1999)
12.
go back to reference Levy, P.S., Stolte, K.: Statistical methods in public health and epidemiology: a look at the recent past and projections for the next decade. Stat. Methods Med. Res. 9, 41–55 (2000)CrossRefMATH Levy, P.S., Stolte, K.: Statistical methods in public health and epidemiology: a look at the recent past and projections for the next decade. Stat. Methods Med. Res. 9, 41–55 (2000)CrossRefMATH
13.
go back to reference Zhang, Z., Chen, K., Ni, H., et al.: Predictive value of lactate in unselected critically ill patients: an analysis using fractional polynomials. J. Thorac. Dis. 6, 995–1003 (2014) Zhang, Z., Chen, K., Ni, H., et al.: Predictive value of lactate in unselected critically ill patients: an analysis using fractional polynomials. J. Thorac. Dis. 6, 995–1003 (2014)
Metadata
Title
Logistic Regression Methods in Selected Medical Information Systems
Authors
Anna Kasperczuk
Agnieszka Dardzinska
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-70004-5_12

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