An intelligent hybrid neuro-fuzzy rule-based system for prognostic decision making in prostate cancer patients

H. Seker; M.O. Odetayo; Dobrila Petrovic; R.N.G. Naguib

doi:10.1109/ITAB.2003.1222519

An intelligent hybrid neuro-fuzzy rule-based system for prognostic decision making in prostate cancer patients

H. Seker, M.O. Odetayo, Dobrila Petrovic, R.N.G. Naguib

School of Computing, Electronics and Maths

Research output: Chapter in Book/Report/Conference proceeding › Chapter

5 Citations (Scopus)

Abstract

A novel hybrid neuro-fuzzy rule-based system is presented for prognostic decision making in prostate cancer patients. The results are further compared with those of multilayer feedforward backpropagation neural networks (MLFFBPNN), fuzzy k-nearest neighbour classifier (FK-NN) and logistic regression (LR).

Original language	English
Title of host publication	Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on
Publisher	IEEE
Pages	230-233
ISBN (Print)	0-7803-7667-6
DOIs	https://doi.org/10.1109/ITAB.2003.1222519
Publication status	Published - 2003

Bibliographical note

This paper is not available on the repository. The paper was given at the 4th International IEEE EMBS Special Topic Conference on, 24-26 April 2003

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10.1109/ITAB.2003.1222519

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An intelligent hybrid neuro-fuzzy rule-based system for prognostic decision making in prostate cancer patients. / Seker, H.; Odetayo, M.O.; Petrovic, Dobrila; Naguib, R.N.G.

Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on. IEEE, 2003. p. 230-233.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

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title = "An intelligent hybrid neuro-fuzzy rule-based system for prognostic decision making in prostate cancer patients",

abstract = "A novel hybrid neuro-fuzzy rule-based system is presented for prognostic decision making in prostate cancer patients. The results are further compared with those of multilayer feedforward backpropagation neural networks (MLFFBPNN), fuzzy k-nearest neighbour classifier (FK-NN) and logistic regression (LR).",

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AU - Naguib, R.N.G.

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AB - A novel hybrid neuro-fuzzy rule-based system is presented for prognostic decision making in prostate cancer patients. The results are further compared with those of multilayer feedforward backpropagation neural networks (MLFFBPNN), fuzzy k-nearest neighbour classifier (FK-NN) and logistic regression (LR).

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BT - Information Technology Applications in Biomedicine, 2003. 4th International IEEE EMBS Special Topic Conference on

PB - IEEE

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An intelligent hybrid neuro-fuzzy rule-based system for prognostic decision making in prostate cancer patients

Abstract

Bibliographical note

UN SDGs

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