TAILIEUCHUNG - Artificial Neural Networks in Cancer Diagnosis, Prognosis, and Patient Management

The potential value of artificial neural networks (ANNs) as a predictor of malignancy has now been widely recognised. The concept of ANNs dates back to the early part of the 20th century; however, their latest resurrection started in earnest in the 1980s when they were applied to many problems in the areas of pattern recognition, control, and optimisation. Here we present a series of articles that emphasise the keen interest displayed by the scientific community in the application of neural networks in the management of human cancers, and also reflect the recent intense activity in this field. The neural systems use prognostic cancer markers as input neurons. | The BIOMEDICAL ENGINEERING Series Series Editor Michael Neuman Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management decision making re prognostic classes for a new cancer patient X I by means of radial basis function neural networks rbfnn confidence_value class_of_cancer_prognosis max a_4 Edited by Raouf . Naguib Gajanan V. Sherbet Artificial Neural Networks in Cancer Diagnosis Prognosis and Patient Management Biomedical Engineering Series Edited by Michael R. Neuman Published Titles Electromagnetic Analysis and Design in Magnetic Resonancer Imaging Jianming Jin Endogenous and Exogenous Regulation and Control of Physiological Systems Robert B. Northrop Artificial Neural Networks in Cancer Diagnosis Prognosis and Treatment Raouf . Naguib and Gajanan V. Sherbet Medical Image Registration Joseph V. Hajnal Derek Hill and David J. Hawkes Introduction to Dynamic Modeling of Neuro-Sensory Systems Robert B. Northrop Forthcoming Titles Noninvasive Instrumentation and Measurement in Medical Diagnosis Robert B. Northrop Handbook of Neuroprosthetic Methods Warren E. Finn and Peter G. .

• Quản trị mạng
• Artificial Neural Networks
• Cancer Diagnosis
• Prognosis
• Molecular Prognostic Factors
• DNA Ploidy
• Cell Cycle Distribution
• Breast Cancer
• Patient Management
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