Artificial neural networks for use in the diagnosis and treatment of breast cancer

Author

Brandt, Jim ; Harris, C. Thomas

fYear

1995

Firstpage

448

Lastpage

453

Abstract

In this paper an outline is given of a modelling approach, using associative memory neural networks (AMNNs), to be used in an intelligent oncology workstation for the improved treatment and diagnosis of breast cancer. This intelligent systems approach is intended to assist in the provision of the most suitable treatment and therapy for breast cancer patients and to seek to add to knowledge in this vital area to yield improved diagnostic and treatment techniques. A major component of the system is a high-dimensional approximator AMNN based on the Adaptive Spline Modelling of Observation Data (ASMOD) algorithm of (Kavli, 1993) which is a constructive learning algorithm used to automatically generate high-dimensional models

Keywords

content-addressable storage; learning (artificial intelligence); medical diagnostic computing; medical expert systems; neural nets; patient diagnosis; patient treatment; splines (mathematics); Adaptive Spline Modelling of Observation Data; associative memory neural networks; breast cancer diagnosis; breast cancer treatment; constructive learning algorithm; high-dimensional approximator neural network; high-dimensional model generation; intelligent oncology workstation; intelligent systems; patient therapy;

fLanguage

English

Publisher

iet

Conference_Titel

Artificial Neural Networks, 1995., Fourth International Conference on

Conference_Location

Cambridge

Print_ISBN

0-85296-641-5

Type

conf

DOI

10.1049/cp:19950598

Filename

497861