Open AccessBreast Cancer Prognosis Using Learning Vector Quantization Neural Network Technique
Author(s) -
W. Abdul Hameed,
Raja Das,
Jitendra Jaiswal
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i4.10.26789
Subject(s) - learning vector quantization , breast cancer , artificial neural network , artificial intelligence , quantization (signal processing) , computer science , disease , vector quantization , machine learning , deep learning , oncology , medicine , pattern recognition (psychology) , cancer , algorithm
A suitable treatment coming after surgery is very much motivated by prognosis - the speculated outcome of the disease. Now-a-days improving prognostic prediction is a challenging task to the doctors. This paper presents prognosis for the breast cancer issues by applying Neural Network Architecture with the dataset for Wisconsin Prognostic Breast Cancer. The accuracy is evaluated by adopting algorithm for Kohonen’s first issue of Learning Vector Quantization to predict the recurrence of the disease within 2 years or beyond and also within 5 years or beyond.