Tuberculosis disease diagnosis using artificial neural networks.

作者: Orhan Er , Feyzullah Temurtas , A Çetin Tanrıkulu , None

DOI: 10.1007/S10916-008-9241-X

关键词:

摘要: Tuberculosis is an infectious disease, caused in most cases by microorganisms called Mycobacterium tuberculosis. Tuberculosis is a great problem in most low income countries; it is …

参考文章(16)
A. M. Santos, B. B. Pereira, J. M. Seixas, F. C. Q. Mello, A. L. Kritski, Neural Networks: An Application for Predicting Smear Negative Pulmonary Tuberculosis Advances in Statistical Methods for the Health Sciences. pp. 275- 287 ,(2007) , 10.1007/978-0-8176-4542-7_18
L. Ozyilmaz, T. Yildirim, Diagnosis of thyroid disease using artificial neural network methods international conference on neural information processing. ,vol. 4, pp. 2033- 2036 ,(2002) , 10.1109/ICONIP.2002.1199031
David E. Rumelhart, James L. McClelland, , Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations Computational Models of Cognition and Perception. ,(1986) , 10.7551/MITPRESS/5236.001.0001
Howard B. Demuth, Martin T. Hagan, Mark Beale, Neural network design ,(1995)
A.B. Watkins, L.C. Boggess, A resource limited artificial immune classifier congress on evolutionary computation. ,vol. 1, pp. 926- 931 ,(2002) , 10.1109/CEC.2002.1007049
Dursun Delen, Glenn Walker, Amit Kadam, Predicting breast cancer survivability: a comparison of three data mining methods Artificial Intelligence in Medicine. ,vol. 34, pp. 113- 127 ,(2005) , 10.1016/J.ARTMED.2004.07.002
Feyzullah Temurtas, A comparative study on thyroid disease diagnosis using neural networks Expert Systems With Applications. ,vol. 36, pp. 944- 949 ,(2009) , 10.1016/J.ESWA.2007.10.010
M. Gori, A. Tesi, On the problem of local minima in backpropagation IEEE Transactions on Pattern Analysis and Machine Intelligence. ,vol. 14, pp. 76- 86 ,(1992) , 10.1109/34.107014
Orhan Er, Feyzullah Temurtas, A Study on Chronic Obstructive Pulmonary Disease Diagnosis Using Multilayer Neural Networks Journal of Medical Systems. ,vol. 32, pp. 429- 432 ,(2008) , 10.1007/S10916-008-9148-6