Artificial neural networks for cancer research: outcome prediction.
The use of artificial neural networks in biological and medical research has increased tremendously in the last few years. Artificial neural networks are being used in cancer research for image processing, the analysis of laboratory data for breast cancer diagnosis, the discovery of chemotherapeutic agents, and for cancer outcome prediction. A neural network generalizes from the input data to patterns inherent in the data, and its uses these patterns to make predictions or to classify. This paper explains how neural networks work, and it shows that a neural network is more accurate at predicting breast cancer patient outcome than the current staging system.
Burke
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Center for Biomedical Modeling Research, Washoe Medical Center, Univ. of Nevada School of Medicine, Reno 89520.
D001943:Breast Neoplasms / Q000175:diagnosis / Q000401:mortality / Q000473:pathology; D016208:Databases, Factual; D005260:Female; D005544:Forecasting; D006801:Humans; D009316:National Institutes of Health (U.S.); D009367:Neoplasm Staging / Q000379:methods; D009369:Neoplasms / Q000175:diagnosis* / Q000401:mortality / Q000473:pathology; D016571:Neural Networks, Computer; D010043:Outcome and Process Assessment, Health Care; D011379:Prognosis; D012372:ROC Curve; D012042:Registries; D015203:Reproducibility of Results; D014481:United States