Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer
Joint Authors
Yang, Huan
Cao, Jia
Zhang, Le
Zheng, Chunqiu
Li, Tian
Xing, Lei
Zeng, Han
Li, Tingting
Chen, Badong
Zhou, Ziyuan
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-16
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
Colorectal cancer (CRC), as a result of a multistep process and under multiple factors, is one of the most common life-threatening cancers worldwide.
To identify the “high risk” populations is critical for early diagnosis and improvement of overall survival rate.
Of the complicated genetic and environmental factors, which group is mostly concerning colorectal carcinogenesis remains contentious.
For this reason, this study collects relatively complete information of genetic variations and environmental exposure for both CRC patients and cancer-free controls; a multimethod ensemble model for CRC-risk prediction is developed by employing such big data to train and test the model.
Our results demonstrate that (1) the explored genetic and environmental biomarkers are validated to connect to the CRC by biological function- or population-based evidences, (2) the model can efficiently predict the risk of CRC after parameter optimization by the big CRC-related data, and (3) our innovated heterogeneous ensemble learning model (HELM) and generalized kernel recursive maximum correntropy (GKRMC) algorithm have high prediction power.
Finally, we discuss why the HELM and GKRMC can outperform the classical regression algorithms and related subjects for future study.
American Psychological Association (APA)
Zhang, Le& Zheng, Chunqiu& Li, Tian& Xing, Lei& Zeng, Han& Li, Tingting…[et al.]. 2017. Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer. Complexity،Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1143591
Modern Language Association (MLA)
Zhang, Le…[et al.]. Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer. Complexity No. 2017 (2017), pp.1-14.
https://search.emarefa.net/detail/BIM-1143591
American Medical Association (AMA)
Zhang, Le& Zheng, Chunqiu& Li, Tian& Xing, Lei& Zeng, Han& Li, Tingting…[et al.]. Building Up a Robust Risk Mathematical Platform to Predict Colorectal Cancer. Complexity. 2017. Vol. 2017, no. 2017, pp.1-14.
https://search.emarefa.net/detail/BIM-1143591
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143591