Next Article in Journal
Somatic Mutation of PIK3CA (H1047R) Is a Common Driver Mutation Hotspot in Canine Mammary Tumors as Well as Human Breast Cancers
Previous Article in Journal
Long Non-Coding RNA MAGI2-AS3 is a New Player with a Tumor Suppressive Role in High Grade Serous Ovarian Carcinoma
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Cancers
Volume 11
Issue 12
10.3390/cancers11122007
cancers-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach

by
Pushpanjali Gupta
1,†,
Sum-Fu Chiang
2,3,†,
Prasan Kumar Sahoo
1,2,*,
Suvendu Kumar Mohapatra
4,
Jeng-Fu You
2,*,
Djeane Debora Onthoni
1,
Hsin-Yuan Hung
2,
Jy-Ming Chiang
2,
Yenlin Huang
5,6 and
Wen-Sy Tsai
2,5
1
Department of Computer Science and Information Engineering, Chang Gung University, Guishan 33302, Taiwan
2
Division of Colon and Rectal Surgery, Chang Gung Memorial Hospital, Linkou 33305, Taiwan
3
Graduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Guishan 33302, Taiwan
4
Volktek Corporation, New Taipei 23553, Taiwan
5
College of Medicine, Chang Gung University, Guishan 33302, Taiwan
6
Department of Anatomic Pathology, Chang Gung Memorial Hospital, Linkou 33305, Taiwan
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Cancers 2019, 11(12), 2007; https://doi.org/10.3390/cancers11122007
Submission received: 14 October 2019 / Revised: 1 December 2019 / Accepted: 9 December 2019 / Published: 12 December 2019
Browse Figures
Versions Notes

Abstract

The prediction of tumor in the TNM staging (tumor, node, and metastasis) stage of colon cancer using the most influential histopathology parameters and to predict the five years disease-free survival (DFS) period using machine learning (ML) in clinical research have been studied here. From the colorectal cancer (CRC) registry of Chang Gung Memorial Hospital, Linkou, Taiwan, 4021 patients were selected for the analysis. Various ML algorithms were applied for the tumor stage prediction of the colon cancer by considering the Tumor Aggression Score (TAS) as a prognostic factor. Performances of different ML algorithms were evaluated using five-fold cross-validation, which is an effective way of the model validation. The accuracy achieved by the algorithms taking both cases of standard TNM staging and TNM staging with the Tumor Aggression Score was determined. It was observed that the Random Forest model achieved an F-measure of 0.89, when the Tumor Aggression Score was considered as an attribute along with the standard attributes normally used for the TNM stage prediction. We also found that the Random Forest algorithm outperformed all other algorithms, with an accuracy of approximately 84% and an area under the curve (AUC) of 0.82 ± 0.10 for predicting the five years DFS.
Keywords: colon cancer; artificial intelligence; machine learning; TNM staging; disease-free survival; prediction colon cancer; artificial intelligence; machine learning; TNM staging; disease-free survival; prediction

Share and Cite

MDPI and ACS Style

Gupta, P.; Chiang, S.-F.; Sahoo, P.K.; Mohapatra, S.K.; You, J.-F.; Onthoni, D.D.; Hung, H.-Y.; Chiang, J.-M.; Huang, Y.; Tsai, W.-S. Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach. Cancers 2019, 11, 2007. https://doi.org/10.3390/cancers11122007

AMA Style

Gupta P, Chiang S-F, Sahoo PK, Mohapatra SK, You J-F, Onthoni DD, Hung H-Y, Chiang J-M, Huang Y, Tsai W-S. Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach. Cancers. 2019; 11(12):2007. https://doi.org/10.3390/cancers11122007

Chicago/Turabian Style

Gupta, Pushpanjali, Sum-Fu Chiang, Prasan Kumar Sahoo, Suvendu Kumar Mohapatra, Jeng-Fu You, Djeane Debora Onthoni, Hsin-Yuan Hung, Jy-Ming Chiang, Yenlin Huang, and Wen-Sy Tsai. 2019. "Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach" Cancers 11, no. 12: 2007. https://doi.org/10.3390/cancers11122007

APA Style

Gupta, P., Chiang, S.-F., Sahoo, P. K., Mohapatra, S. K., You, J.-F., Onthoni, D. D., Hung, H.-Y., Chiang, J.-M., Huang, Y., & Tsai, W.-S. (2019). Prediction of Colon Cancer Stages and Survival Period with Machine Learning Approach. Cancers, 11(12), 2007. https://doi.org/10.3390/cancers11122007

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop