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Death prediction and analysis using web mining techniques

Healthcare sector today generate a large amount of complex data about death cause, disease diagnosis, electronic patient records, etc. In this paper prediction and the causes of death event is done using web mining techniques. In the proposed approach, large-scale digital histories are captured for duration of 18 years from news reports of Queensland Government archive to make real-time predictions about the likelihoods of future death and disease events of interest. In addition to the news corpora, data from freely available web resources and multiple web resources are used. Death prediction is performed using various classifiers and results are analyzed using error as a metric. Experimental results demonstrate the efficiency of the best forecasting and prediction.