Toggle Main Menu Toggle Search

Open Access padlockePrints

A hybrid system for nodal involvement assessment in breast cancer patients

Lookup NU author(s): Dan Petrovici, Dr Madurai Lakshmi, Dr Gajanan Sherbet


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


This paper presents a new hybrid system developed for nodal involvement assessment in breast cancer patients. The hybrid system integrates a neural network and fuzzy rule-based system learning methods. The data used in this study were collected from 100 women who were clinically diagnosed with breast cancer in the form of carcinoma or benign conditions. The data set contains seven different histological and cytological factors, and two nodal outputs (positive and negative nodal status) to be predicted for nodal involvement assessment in breast cancer patients. The hybrid system yielded the highest predictive accuracy of 73%, compared with statistical, neural networks and fuzzy logic methods. The overall results are encouraging and reveal the efficiency of the hybrid system.

Publication metadata

Author(s): Seker H, Odetayo MO, Petrovic D, Naguib RNG, Bartoli C, Alasio L, Lakshmi MS, Sherbet GV

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Annual International Conference of the IEEE Engineering in Medicine and Biology

Year of Conference: 2002

Pages: 1049-1050

ISSN: 1094-687X

Publisher: IEEE


DOI: 10.1109/IEMBS.2002.1106270

Library holdings: Search Newcastle University Library for this item

ISBN: 0780376129