Disease Predication of Cardio- Vascular Diseases, Diabetes and Malignancy in Lungs Based on Data Mining Classification Techniques - Dey, Monali; Rautaray, Siddharth Swarup (International Journal of Computer Sciences and Engineering, 2014)
Data mining technology provides a user oriented approach to extract the hidden information from the large database. There are different algorithms used in data mining techniques like decision tree, Bayesian classifier, naive Bayes, neural network, , clustering etc. Data mining in healthcare medicine deals with learning models to predict patient's disease. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The main goal of this paper is to analyze and implement the data mining algorithms using WEKA tool and comparison between c4.5 and Bayesian classifier.