International Journal of System & Software Engineering

Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Multi Disease Prediction Using Data Mining Techniques


Affiliations
1 Department of Computer Science, Karpagam University, Coimbatore, Tamil Nadu, India
2 Department of Information Technology, Karpagam University, Coimbatore, Tamil Nadu, India
     

   Subscribe/Renew Journal


Data mining techniques are used for a variety of applications. In healthcare industry, data mining plays an important role in predicting diseases. For detecting a disease number of tests should be required from the patient. But using data mining technique the number of tests can be reduced. This reduced test plays an important role in time and performance. This paper analyzes data mining techniques which can be used for predicting different types of diseases. This paper reviewed the research papers which mainly concentrate on predicting heart disease, Diabetes and Breast cancer etc.

Keywords

Data Mining, Classification, Naive Bayes, J48, Decision Tree.
Subscription Login to verify subscription
User
Notifications
Font Size


  • http://www.mayoclinic.org/diseases-conditions/heart-disease/basics/definition/con-20034056

  • http://www.idf.org/about-diabetes

  • http://www.cancer.org/cancer/breastcancer/detailedguide/breast-cancer-what-is-breast-cancer

  • Kumara, M., Vohra, R., Arora, A. (2014). Prediction of diabetes using Bayesian network. International Journal of Computer Science and Information Technologies, 5(4), 5174-5178.

  • Thirumal, P. C., & Nagarajan, N. (2015). Utilization of data mining techniques for diagnosis of diabetes mellitus - A case study. ARPN Journal of Engineering and Applied Sciences, January, 10(1), 8-13.

  • Gomathi, K. (2012). An empirical study on breast cancer using data mining techniques. International Journal of Research in Computer Application & Management, July, 2(7), 97-102.

  • Witten, H. I., & Frank, E. (2005). Data Mining: Practical Machine Learning Tools and Techniques, (2nd Ed), Morgan Kaufmann Publishers.

  • Witten, I. H. & Frank, E. (2005). Data Mining: Practical machine learning tools and techniques, (2nd Ed.) San Fransisco: Morgan Kaufmann.

  • WEKA: Data Mining Software in Java. Retrieved from http://www.cs.waikato.ac.nz/ml/weka/

  • Delen, D., Walker, G., & Kadam, A. (2005). Predicting breast cancer survivability: A comparison of three data mining methods. Artificial Intelligence in Medicine, June, 34(2), 113-127.


Abstract Views: 288

PDF Views: 3




  • Multi Disease Prediction Using Data Mining Techniques

Abstract Views: 288  |  PDF Views: 3

Authors

K. Gomathi
Department of Computer Science, Karpagam University, Coimbatore, Tamil Nadu, India
D. Shanmuga Priya
Department of Information Technology, Karpagam University, Coimbatore, Tamil Nadu, India

Abstract


Data mining techniques are used for a variety of applications. In healthcare industry, data mining plays an important role in predicting diseases. For detecting a disease number of tests should be required from the patient. But using data mining technique the number of tests can be reduced. This reduced test plays an important role in time and performance. This paper analyzes data mining techniques which can be used for predicting different types of diseases. This paper reviewed the research papers which mainly concentrate on predicting heart disease, Diabetes and Breast cancer etc.

Keywords


Data Mining, Classification, Naive Bayes, J48, Decision Tree.

References