CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Predicting Lung Cancer Survivability using SVM and Logistic Regression Algorithms

by Animesh Hazra, Nanigopal Bera, Avijit Mandal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 174 - Number 2
Year of Publication: 2017
Authors: Animesh Hazra, Nanigopal Bera, Avijit Mandal
10.5120/ijca2017915325

Animesh Hazra, Nanigopal Bera, Avijit Mandal . Predicting Lung Cancer Survivability using SVM and Logistic Regression Algorithms. International Journal of Computer Applications. 174, 2 ( Sep 2017), 19-24. DOI=10.5120/ijca2017915325

@article{ 10.5120/ijca2017915325,
author = { Animesh Hazra, Nanigopal Bera, Avijit Mandal },
title = { Predicting Lung Cancer Survivability using SVM and Logistic Regression Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2017 },
volume = { 174 },
number = { 2 },
month = { Sep },
year = { 2017 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume174/number2/28380-2017915325/ },
doi = { 10.5120/ijca2017915325 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:21:06.106356+05:30
%A Animesh Hazra
%A Nanigopal Bera
%A Avijit Mandal
%T Predicting Lung Cancer Survivability using SVM and Logistic Regression Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 174
%N 2
%P 19-24
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

One of the most common and leading cause of cancer death in human beings is lung cancer. The advanced observation of cancer takes the main role to inflate a patient’s probability for survival of the disease. This paper inspects the accomplishment of support vector machine (SVM) and logistic regression (LR) algorithms in predicting the survival rate of lung cancer patients and compares the effectiveness of these two algorithms through accuracy, precision, recall, F1 score and confusion matrix. These techniques have been applied to detect the survival possibilities of lung cancer victims and help the physicians to take decisions on the forecast of the disease.

References
  1. Wolfgang A. Weber, Constantine A. Gatsonis, P. David Mozley, Lucy G. Hanna, Anthony F. Shields, Denise R. Aberle, Ramaswamy Govindan, Drew A. Torigian, Joel S. Karp, Jian Q. (Michael) Yu, Rathan M. Subramaniam, Robert A. Halvorsen, and Barry A. Siegel “Repeatability of18 F-FDG PET/CT in Advanced Non–Small Cell Lung Cancer: Prospective Assessment in 2 Multicenter Trials”, The journal of Nuclear Medicine(JNN), DOI: 10.2967/jnumed.114.147728, Apr. 2015.
  2. Runxuan Zhang, Guang-Bin Huang, N. Sundararajan, and P Saratchandran, “Multicategory Classification Using an Extreme Learning Machine for Microarray Gene Expression Cancer Diagnosis”, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 4, Issue 3, 2007.
  3. Daniel Morgensztern, Meghan J. Campo, Suzanne E. Dahlberg, Robert C. Doebele, M.D., EdwardGaron, David E. Gerber, Sarah B. Goldberg, Peter S. Hammerman, Rebecca Heist, Thomas Hensing, Leora Horn, Suresh S. Ramalingam, Charles M. Rudin, Ravi Salgia, LeciaSequist, Alice T. Shaw, George R. Simon, Neeta Somaiah, David R. Spigel, John Wrangle, David Johnson, Roy S. Herbst, Paul Bunn, and Ramaswamy Govindan, “Molecularly Targeted Therapies in Non-Small-Cell Lung Cancer Annual Update 2014”,J Thorac Onc
  4. Michael K. Showe, Andrew V. Kossenkov, and Louise C. Showe, “The Peripheral Immune Response and Lung Cancer Prognosis”, Oncoimmunology,1(8),1414–1416, doi: 10.4161/onci.21093, 2012.
  5. Fan Zhang, Yang Song, Weidongcai, Yun Zhou, Shimin Shan, and Dagan Feng, “Context Curves for Classification of Lung Nodule Images”, IEEE/ Digital Image Computing: Techniques and Applications (DICTA), DOI:10.1109/DICTA.2013.6691494, 2013.
  6. Avci E, “A New Expert System for Diagnosis of Lung Cancer: GDA-LS_SVM”, J Med Syst, 36(3):2005-9. doi: 10.1007/s10916-011-9660-y, 2012.
  7. Van Belle V, Pelckmans K, Van Huffel S, and Suykens JA, “Support Vector Methods for Survival Analysis: A Comparison Between Ranking and Regression Approaches”, Artif Intell Med, 53(2):107-18, doi: 10.1016/j.artmed.2011.06.006, Aug. 2011.
  8. Lee Y, Seo JB, Lee JG, Kim SS, Kim N, and Kang SH, “Performance Testing of Several Classifiers for Differentiating Obstructive Lung Diseases Based on Texture Analysis at High-Resolution Computerized Tomography (HRCT)”, Compute Methods Programs Biomed, 93(2):206-15.doi: 10.1016/j.cmpb.2008.10.008, Dec. 2008.
  9. Jonghyuck Lim, Namkug Kim, JoonBeomSeo, Young Kyung Lee, Youngjoo Lee, and Suk-Ho Kang, “Regional Context-Sensitive Support Vector Machine Classifier to Improve Automated Identification of Regional Patterns of Diffuse Interstitial Lung Disease”, J Digit Imaging, 24(6): 1133–1140, doi: 10.1007/s10278-011-9367-0, 2011.
  10. Vijayalakshmi Sampath, Andrew Flagel, Carolina Figueroa, “A Logistic Regression Model to Predict Freshmen Enrollments”, Paper SD-016.
  11. NSCLC - Radiomics [online] https://wiki.cancerimagingarchive.net/display/Public/NSCLC-Radiomics; jsessionid=84D480480E80C9EC1950 26 ED04D95433 [Dataset].
  12. Melissa J. Azur, Elizabeth A. Stuart, Constantine Frangakis, and Philip J. Leaf, “Multiple Imputation by Chained Equations: What is it and how does it work?”, PMC, Int J Methods Psychiatr Res, 20(1): 40–49; Mar. 2011.
  13. MM Mukaka,“Statistics Corner: A guide to appropriate use of Correlation coefficient in medical research”, Malawi Med J, 24(3): 69–71, 2012.
  14. Peng Guan, Desheng Huang, Miao He, and Baosen Zhou, “Lung Cancer Gene Expression Database Analysis Incorporating Prior Knowledge with Support Vector Machine-Based Classification Method”, J Exp Clin Cancer Res, 28(1): 103, 2009.
  15. A. K. Santra, and C. Josephine Christy, “Genetic Algorithm and Confusion Matrix for Document Clustering”, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No. 2, 2012.
  16. Simple guide to confusion matrix terminology - Data School [online] http://www.dataschool.io/simple-guide-to-confusion-mat rixterminology/.
Index Terms

Computer Science
Information Sciences

Keywords

Lung Cancer Logistic Regression SVM Confusion Matrix.

Powered by PhDFocusTM