Dipankar Dutta

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— The aim of the paper is to study a real coded multi objective genetic algorithm based K-clustering, where K represents the number of clusters, may be known or unknown. If the value of K is known, it is called K-clustering algorithm. The searching power of Genetic Algorithm (GA) is exploited to get for proper clusters and centers of clusters in the feature(More)
Traumatic brain injury (TBI) affects 5.3 million Americans annually. Despite the many long-term deficits associated with TBI, there currently are no clinically available therapies that directly address the underlying pathologies contributing to these deficits. Preclinical studies have investigated various therapeutic approaches for TBI: two such approaches(More)
—In the paper, real coded multi objective genetic algorithm based K-clustering method has been studied where K represents the number of clusters known apriori. The searching power of Genetic Algorithm (GA) is exploited to search for suitable clusters and cluster modes so that intra-cluster distance (Homogeneity, H) and inter-cluster distances (Separation,(More)
BACKGROUND The diagnosis of Transient Ischaemic Attack (TIA) can be difficult and 50-60% of patients seen in TIA clinics turn out to be mimics. Many of these mimics have high ABCD2 scores and fill urgent TIA clinic slots inappropriately. A TIA diagnostic tool may help non-specialists make the diagnosis with greater accuracy and improve TIA clinic triage.(More)
—We can classify clustering into two categories. In K Clustering, we know the number of clusters or K. In other category of clustering, K in unknown. In this paper we have considered the first category only. We can broadly classify features within a data set into continuous and categorical. Here we have considered data set with continuous features only.(More)