期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2011
卷号：8
期号：6
出版社：IJCSI Press
摘要：Chikungunya (CHIK) virus, similar to Dengue pose a serious threat in Tropics, because of the year-round presence of Aedes mosquito vectors .The use of machine learning techniques and data mining algorithms have taken a great role in the diagnosis and prognosis of many health diseases. But a very few work has been initialized in this arboviral medical informatics. Our focus is to observe clinical and physical diagnosis of chikungunya viral fever patients and its comparison with dengue viral fever. Our project aims to integrate different sources of information and to discover patterns of diagnosis, for predicting the viral infected patients and their results. The scope is mainly in the classification problem of these often confused arboviral infections. This study paper summarizes various review and technical articles on arboviral diagnosis and prognosis. In this paper we present an overview of the current research being carried out using the data mining techniques to enhance the arboviral disease diagnosis and prognosis. This paper is not intended to provide a comprehensive overview of medical data mining but rather describes some areas which seem to be important from our point of view for applying machine learning in medical diagnosis for our real viral dataset.
关键词：Data Mining; Medical data; Machine learning algorithms; Diagnosis; Arbovirus
