Small-area studies offer a powerful epidemiological approach to study disease patterns at
the population level and assess health risks posed by environmental pollutants. They …

In the last decade, data warehousing became the most important technology in the field of
decision support especially related to critical situations. Most of Decision Support Systems …

Recently, spatial data mining plays a vital role because of its pressing need in the real world
applications. Among the wide range of applications the nature disaster diagnosis is the most …

Spatial data mining is the quantitative study of phenomena that are located in space. This
paper investigates methods of mining patterns of a complex spatial data set (which generally …

Data mining techniques found applications in many areas since their development. New
techniques or combination of techniques are created continuously. Techniques like …

A data warehouse is a powerful repository of large, multi dimensional data cubes that
answers complex queries and helps in decision making process. Data warehouses often act …

In this research work, we have presented an illustration of spatial ecological predictive
modelling. We focused on the unique features that distinguish spatial data mining from …

This paper shows the experience of a specialized data mining process that integrates
mortality data collected by the official censuses of 2000 and 2010. The objective is the …

Not only do cluster randomized trials require a larger sample size than individually
randomized trials, they also face many additional complexities. The potential for …