Data mining application for predictive learning from visiting nurse association data

In the following paper the process of knowledge generation from the Visiting Nurse Association database for elderly care is explored. This inquiry is concerned with predicting falls. Predicting which patients are likely to fall can assist the clinician in the identification of high-risk patients and suggest the need for early falls prevention programs. The entire data mining process is described beginning with data gathering followed by cleaning, aggregation, and integration. Issues faced while conducting the research are discussed Results of decision trees and decision rules, and artificial neural networks used to predict falls are presented