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.
| Original language | English |
|---|---|
| Pages (from-to) | 583-584 |
| Journal | European Journal of Gynaecological Oncology |
| Volume | 21 |
| Issue number | 6 |
| Publication status | Published - 2000 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- artificial neural networks
- survival prediction
- ovarian carcinoma
- preliminary results
ASJC Scopus subject areas
- General Health Professions
- General Medicine
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