Data Mining Patterns: New Methods and Applications
Data Mining Patterns: New Methods and Applications
Development of a data warehouse for lymphoma cancer diagnosis and treatment decision support
MCBC'09 Proceedings of the 10th WSEAS international conference on Mathematics and computers in biology and chemistry
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This proposal is based on the implementation and the development of tools to analyse the decision making indicators in the epidemiology for the ministry of the heath. We introduced new tools of data warehouse and data mining to improve epidemiological knowledge specific to the Leishmaniasis in South of Morocco. In order to contribute to the planning of the prevention and the control against leishmaniasis in Morocco, we developed an information system to facilitate the decision-making process, access to the information and data storage in the data warehouse. In phase I, we have considered the density of the sandflies population when taking into account the time and climate change. In phase II, We have extended the work by including the transmission of Leishmaniasis to humans, we are interested in patients with suspected Leishmania infection. This allowed us to develop two different patterns. The concept of Data Mining is used to select, to explore and to transform our epidemic data to a prediction index. In this paper we review the type of decision aids which has been successfully implemented and that we have provided to the responsible of the population health to make better decisions.