Pattern recognition of occupational cancer using neural networks

Vincent To Yee Ng, Raymond Fang, Joel Bert, Pierre Band, Laurence Svirchev, Anya Keefe

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This paper presents an application of multi-layered neural networks to occupational epidemiology for the Pulp and Paper industry. Various architectures of Feedforward Networks with and without hidden layers have been tested to examine the relationships between occupational exposure and cancer. The inputs to the networks consist of chemical exposures derived from epidemiological studies. The outputs are the cancer types of the patients. The results of the classification performances demonstrate that an appropriate network architecture with some pre-processing of the exposures might lead to more efficient results.
Original languageEnglish
Title of host publicationIEEE Pac Rim Conf Commun Comput Signal Process
PublisherPubl by IEEE
Pages296-300
Number of pages5
ISBN (Print)0780312198
Publication statusPublished - 1 Jan 1993
Externally publishedYes
EventProceedings of the IEEE 1993 Pacific Rim Conference on Communications, Computers and Signal Processing - Victoria, BC, Canada
Duration: 19 May 199321 May 1993

Conference

ConferenceProceedings of the IEEE 1993 Pacific Rim Conference on Communications, Computers and Signal Processing
Country/TerritoryCanada
CityVictoria, BC
Period19/05/9321/05/93

ASJC Scopus subject areas

  • General Engineering

Fingerprint

Dive into the research topics of 'Pattern recognition of occupational cancer using neural networks'. Together they form a unique fingerprint.

Cite this