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Murine Model for Non-invasive Imaging to Detect and Monitor Ovarian Cancer Recurrence
Published on: November 2, 2014
Artificial neural networks and survival prediction in ovarian carcinoma
1Dept. of Gynaecological Oncology, The Birmingham Womens Hospital, Edgbaston, UK.
European Journal of Gynaecological Oncology
|February 24, 2001
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.

