Group testing in the development of an expanded cancer staging system

Dechang Chen*, Donald Henson, Kai Xing, Li Sheng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Though the TNM (Tumor, Lymph Node, Metastasis) is a widely used staging system for predicting the outcome of cancer patients, it is limited in prediction mainly because it does not integrate multiple prognostic factors. Expanding the TNM now becomes possible due to availability of large cancer patient datasets. In this paper, we introduce a group testing algorithm that can be used to add new prognostic factors while preserving the TNM staging system. Our approach starts with survival and evaluates its relation to potential prognostic factors individually and in various combinations. A demonstration is given for lung cancer.

Original languageEnglish
Title of host publicationProceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008
Pages589-594
Number of pages6
DOIs
StatePublished - 2008
Externally publishedYes
Event7th International Conference on Machine Learning and Applications, ICMLA 2008 - San Diego, CA, United States
Duration: 11 Dec 200813 Dec 2008

Publication series

NameProceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008

Conference

Conference7th International Conference on Machine Learning and Applications, ICMLA 2008
Country/TerritoryUnited States
CitySan Diego, CA
Period11/12/0813/12/08

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