Knowledge Attitudes and Practices About Malaria in Chennai Population

Data mining refers to extracting or mining knowledge from large amounts of data. Data mining is multidisciplinary field, drawing work from area including data base technology, artificial intelligence machine learning neural network, statistical, pattern mining, knowledge based system, knowledge acquisition, information retrieval, high performance computing and data visualization. Data mining plays an important role in the knowledge discovery process in medical data base. Using data mining techniques Malaria diseases prevention of knowledge, attitude and practice we can be easily prediction from people attributes and various diseases of symptoms. Malaria remains one of the most causes of maternal and child morbidity and mortality in Tamilnadu population, despite the availability of effective interaction. This objective of this study was to learn the data mining knowledge discovery the techniques for prediction of KAP (knowledge attitude and practice) on fever diseases symptoms, prevention and awareness to develop the health care in our society. This study aims to describe the knowledge attitude, and practices towards malaria among rural, urban and sub urban peoples and to determine scoring predictors of urban people's of knowledge and practice. A multistage, stratified, random sample method was applied. A total of 1500 peoples, each group have 500 peoples completed confidential self administrated questioner. KAP towards malaria deficient among target populations, especially among urban, sub urban and rural peoples. Information, education and communication activity indicated to create awareness among the community.