Are neural networks best used to help logistic regression? An example from breast cancer survival analysis

Author(s):  
P.J.G. Lisboa ◽  
H. Wong
Author(s):  
Venkateswara Rao Mudunuru ◽  
Leslaw A. Skrzypek

In the field of medicine, several recent studies have shown the value of Artificial Neural Networks, decision trees, logistic regression are playing a major role as the predictor, and classification methods. The research has been expanded to estimate the incidence of breast, lung, liver, ovarian, cervical, bladder and skin cancer. The main aim of this paper is to develop models of logistic regression, Artificial Neural Networks, and Decision trees using the same input and output variables and to compare their success in predicting breast cancer survival in woman. To find the best model for breast cancer survival, the sensitivity and specificity of all these models are measured and evaluated with their respective confidence intervals and the ROC values.


2005 ◽  
Vol 97 (16) ◽  
pp. 1195-1203 ◽  
Author(s):  
Yu Shen ◽  
Ying Yang ◽  
Lurdes Y. T. Inoue ◽  
Mark F. Munsell ◽  
Anthony B. Miller ◽  
...  

2013 ◽  
Vol 9 (5) ◽  
pp. e1003047 ◽  
Author(s):  
Erhan Bilal ◽  
Janusz Dutkowski ◽  
Justin Guinney ◽  
In Sock Jang ◽  
Benjamin A. Logsdon ◽  
...  

2018 ◽  
Vol 29 ◽  
pp. ix6
Author(s):  
S. Pashaei ◽  
R. Dolatkhah ◽  
Z. Sanaat ◽  
P. Jabbaripour ◽  
G.H. de Bock

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