IMR Press / EJGO / Volume 21 / Issue 6 / pii/2000236

European Journal of Gynaecological Oncology (EJGO) is published by IMR Press from Volume 40 Issue 1 (2019). Previous articles were published by another publisher on a subscription basis, and they are hosted by IMR Press on imrpress.com as a courtesy and upon agreement with S.O.G.

Open Access Original Research

Artificial neural networks and survival prediction in ovarian carcinoma

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1 Department of Gynaecological Oncology, The Birmingham Womens Hospiral, Binningham, UK
2 Department of Computer Science and Applied Mathematics, Aston University, Binningham, UK
3 Department of Public Health and Epidemiology, University of Birmingham, Binningham, UK
Eur. J. Gynaecol. Oncol. 2000, 21(6), 583–584;
Published: 10 December 2000
Abstract

The standard use of known survival predictors for ovarian cancer in clinical practice are primarily based on disease stage. This does not permit a real individualization of a patient's potential outcome. This study assessed the value of neural networks to refine the prediction of survival based only on information gleaned at primary surgery. The possibility exists that such methods may permit further elucidation of outcome and influence management.

Keywords
Ovarian cancer
Prognosis
Neural network
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