DocumentCode :
2007833
Title :
Group Testing in the Development of an Expanded Cancer Staging System
Author :
Chen, Dechang ; Xing, Kai ; Henson, Donald ; Sheng, Li
Author_Institution :
Div. of Epidemiology & Biostat., Uniformed Services Univ. of the Health Sci., Bethesda, MD
fYear :
2008
fDate :
11-13 Dec. 2008
Firstpage :
589
Lastpage :
594
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.
Keywords :
cancer; data analysis; medical diagnostic computing; tumours; cancer patient dataset; computer-based prognostic system; expanded cancer staging system; group testing algorithm; prognostic factor; tumor lymph node metastasis; Cancer; Databases; Diseases; Lungs; Lymph nodes; Machine learning; Medical treatment; Metastasis; Neoplasms; System testing; TNM; lung cancer; survival function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Applications, 2008. ICMLA '08. Seventh International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-0-7695-3495-4
Type :
conf
DOI :
10.1109/ICMLA.2008.38
Filename :
4725034
Link To Document :
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