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Artificial Neural Networks for use in the Diagnosis and Treatment of Breast Cancer

Artificial Neural Networks for use in the Diagnosis and Treatment of Breast Cancer
Artificial Neural Networks for use in the Diagnosis and Treatment of Breast Cancer
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 which is a constructive learning algorithm used to automatically generate high-dimensional models.
448--453
Bridgett, N.A.
25b96061-a19f-46cf-bef4-b63b56fb5fe1
Brandt, J.
fe36e0bd-893a-4b42-86f6-d0b6c183b8db
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Bridgett, N.A.
25b96061-a19f-46cf-bef4-b63b56fb5fe1
Brandt, J.
fe36e0bd-893a-4b42-86f6-d0b6c183b8db
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Bridgett, N.A., Brandt, J. and Harris, C.J. (1995) Artificial Neural Networks for use in the Diagnosis and Treatment of Breast Cancer. 4th Int. Conf. on Artificial Neural Networks. 448--453 .

Record type: Conference or Workshop Item (Other)

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 which is a constructive learning algorithm used to automatically generate high-dimensional models.

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More information

Published date: June 1995
Additional Information: Conf. Pub. No. 409 Organisation: IEE Address: Cambridge, UK
Venue - Dates: 4th Int. Conf. on Artificial Neural Networks, 1995-01-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 250241
URI: http://eprints.soton.ac.uk/id/eprint/250241
PURE UUID: f40ac09e-5f86-416e-a103-34dca0738d8a

Catalogue record

Date deposited: 04 May 1999
Last modified: 22 Jul 2022 17:55

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Contributors

Author: N.A. Bridgett
Author: J. Brandt
Author: C.J. Harris

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