Publication Type : Conference Proceedings
Publisher : IEEE
Source : 2019 IEEE International ConferenceonElectrical,ComputerandCommunicationTechnologies(ICECCT),2019,pp.1- 4
Url : https://www.scopus.com/record/display.uri?eid=2-s2.0-85074371030&origin=resultslist
Campus : Amritapuri
School : School of Computing
Center : Computational Linguistics and Indic Studies
Year : 2019
Abstract : The growth of cancerous cells in lungs is called lung cancer. The mortality rate of both men and women has expanded due to the increasing rate of incidence of cancer. Lung cancer is a disease where cells in the lungs multiply uncontrollably. Lung cancer cannot be prevented but its risk can be reduced. So detection of lung cancer at the earliest is crucial for the survival rate of patients. The number of chain- smokers is directly proportional to the number of people affected with lung cancer. The lung cancer prediction was analysed using classification algorithms such as Naive Bayes, SVM, Decision tree and Logistic Regression. The keyobjective of this paper is the early diagnosis of lung cancer by examining the performance of classification algorithms.
Cite this Research Publication : R. P.R., R. A. S. Nair and V. G., "A Comparative Study of Lung Cancer Detection using Machine Learning Algorithms," 2019 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT), 2019, pp. 1-4, doi: 10.1109/ICECCT.2019.8869001.