Artificial Neural Networks in Cancer Recurrence Prediction

Author

Ritthipravat, Panrasee

Author_Institution

Biomed. Eng. Programme, Mahidol Univ., Nakornpathom

Volume

2

fYear

2009

fDate

22-24 Jan. 2009

Firstpage

103

Lastpage

107

Abstract

This paper aims to review the use of artificial neural networks (ANNs) in prediction of cancer recurrence. The sources of publications were randomly selected from PUBMED database, IEEE explore, and the google search engine with the keywords for searching as ldquorecurrencerdquo or ldquorelapserdquo or ldquodisease freerdquo + ldquoneural networkrdquo + ldquocancerrdquo. Increasing of the predictive performance was considered. In addition, handling incomplete data and feature selection techniques usually employed in this application were examined.

Keywords

cancer; medical information systems; neural nets; search engines; Google search engine; IEEE explore; PUBMED database; artificial neural networks; cancer recurrence prediction; feature selection; incomplete data; predictive performance; Artificial neural networks; Biomedical engineering; Biomedical imaging; Cancer; Diseases; Medical diagnostic imaging; Neural networks; Neurons; Recurrent neural networks; Search engines; cancer recurrence; feature selection; incomplete data; neural networks; relapse;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Engineering and Technology, 2009. ICCET '09. International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-3334-6

Type

conf

DOI

10.1109/ICCET.2009.84

Filename

4769567