Title :
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
fDate :
30 Oct-2 Nov 1997
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 1997. Proceedings of the 19th Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-4262-3
DOI :
10.1109/IEMBS.1997.756514
