Total views : 152
Detection of Lung Cancer in Smokers and Non- Smokers by Applying Data Mining Techniques
Objective: The data of medical science is increasing rapidly from the last few years. Extensive information related to any disease and its symptom can be extracted, such information can be used for early detection of diseases and to overcome the disease in better way. In this research we are focusing on lung cancer detection at earlier stage. Methods/Statistical Analysis: To discover the meaningful knowledge from the dataset for the health professionals to find the disease at earlier stage with low cost. In this regard, personal characteristics like age, gender, socio economic factors were considered by applying C5.0 algorithm for the development of model. Findings: We found that in Pakistan, lung cancer ratio is increasing in Non-Smoker, previously occurrence ratio was 20% and 80% in Non-Smoker and Smokers respectively but in this research ratio is 22% and 78%. Dataset was taken from SKMCH & RC database. Application/Improvements: Results of this research will be useful for the oncologists; research will be extended in near future on different datasets of lung cancer to diagnose the reasons of lung cancer in non-smokers.
Classification, C5.0, Data Mining, Decision Tree, Lung Cancer, Pre-Processing
- Shams K, Frashita M. Data Warehousing Toward Knowledge Management. Topics in Health Information Management.2001; 21(3):24-32.
- Kharya S. Using data mining techniques for diagnosis and prognosis of cancer disease. International Journal of Computer Science Engineering and Information Technology.2012; 2(2):55-8.
- Krishnaiah V, Narsimha G, Chandra NS. Diagnosis of Lung Cancer Prediction System Using Data Mining Classification Techniques. International Journal of Computer Science and Information Technologies. 2013; 4(1):39-44.
- Ahmed K, Emran AA, Jesmin T, Mukti RF, Rahman MDZ, Ahmed F. Early Detection of Lung Cancer Risk Using Data Mining. Asian Pacific Journal of Cancer Prevention. 2013; 14(1):595-97. Crossref
- Thangaraju P, Barkavi G, Karthikeyan T. Mining Lung Cancer Data for Smokers and Non-Smokers by Using Data Mining Techniques. International Journal of Advanced Research in Computer and Communication Engineering.2014; 3(7):7622-5.
- Kaur H, Wasan SK. Empirical Study on Applications of Data Mining Techniques in Healthcare. Journal of Computer Science. 2006; 2(2):194-200. Crossref
- Pandya R, Pandya J. C5.0 algorithm to improved decision tree with feature selection and reduced error pruning.International Journal of Computer Applications. 2015; 117(16):18-51.
- Gharehchopogh FS. Application of decision tree algorithm for data mining in healthcare operations a case study. International Journal of Computer Applications. 2012; 52(6):21-4.
- Han J, Kamber M. Data mining concepts and techniques.2nd Edition. University of Illinois at Urbana-Champaign; 2006. p. 1-28.
- There are currently no refbacks.
This work is licensed under a Creative Commons Attribution 3.0 License.