Jay Gholap

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In spite of significant progress in the area of data management and integration, heterogeneous nature of clinical data makes it challenging to develop a unified view of clinical data. Therefore, a central question we are trying to address is how we can utilize data analytics to discover insightful knowledge from the scattered & large amount of clinical(More)
Agricultural research has been profited by technical advances such as automation, data mining. Today ,data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft wares are available, but data mining in agricultural soil datasets is a relatively a young research field. The large(More)
Big Data deals with enormous volumes of complex and exponentially growing data sets from multiple sources. With rapid growth in technology, we are now able to generate immense amount of data in almost any field imaginable including physical, biological and biomedical sciences. With the diversity and amount of data in health care industry there is an(More)
This paper proposes a collaborative data mmmg technique to provide multi-level analysis from clinical trials data. Clinical trials for clinical research and drug development generate large amount of data. Due to dispersed nature of clinical trial data, it remains a challenge to harness this data for analytics. In this paper, we propose a novel method using(More)
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