Prognostic neuroclassification of prostate cancer patients

Author

Naguib, R.N.G. ; Hamdy, F.C.

Author_Institution

Dept. of Electr. & Electron. Eng., Newcastle upon Tyne Univ., UK

Volume

3

fYear

1997

fDate

30 Oct-2 Nov 1997

Firstpage

1003

Abstract

This paper assesses the value of using artificial neural networks in the analysis of clinical and experimental prognostic factors and in the prediction of response to treatment and outcome in prostate cancer. 38 patients are considered in this study. The investigation includes a number of established and experimental factors with 3 clinical outcomes: (a) no response to initial treatment, (b) disease relapse and progression, and (c) sustained complete response to treatment. An overall classification rate of 89.5% is achieved together with equally high sensitivity and specificity rates

Keywords

biological organs; cancer; neural nets; patient treatment; artificial neural networks; clinical prognostic factors; disease progression; disease relapse; experimental prognostic factors; prognostic neuroclassification; prostate cancer patients; sensitivity rate; specificity rate; treatment response prediction; Artificial neural networks; Diseases; Immune system; Medical treatment; Metastasis; Neural networks; Neurons; Prostate cancer; Sensitivity and specificity; Tumors;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1094-687X

Print_ISBN

0-7803-4262-3

Type

conf

DOI

10.1109/IEMBS.1997.756514

Filename

756514