Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/2996
Title: Big data analytics of genomic and clinical data for diagnosis and prognosis of cancer
Authors: Patel, Veeresh
Bhardwaj, Trishansh
Adhil, Mohammad
Talukder, Asoke K.
Keywords: Diagnosis
knowledge base
Issue Date: 2015
Publisher: 2015 International Conference on Computing for Sustainable Global Development, INDIACom 2015
Abstract: Sooner the Cancer is diagnosed, better the chances of overall survival. Diagnosis and Prognosis are the two major challenging aspects which are to be addressed in treating cancer. Early diagnosis helps treating cancer before they become metastatic; in addition, prognosis will reveal the survival pattern for different attributes i.e., for specific drug, before and after the treatment. Better the diagnosis and prognosis, better the treatment outcome for Cancer. The very high-throughput technologies like NGS generatesexome data of a single cancer patient that ranges from 10 Giga bytes to 15 Giga bytes. This large amount of Omics data can only be analyzed and interpreted using data-sciences techniques and big-data computational models. Here we present a clinical expert system for predicting the outcome of cancer patients from big-data genomics using the inference engine which makes decision from our in-house knowledge base.
Description: NITW
URI: http://localhost:8080/xmlui/handle/123456789/2996
Appears in Collections:Computer Science & Engineering

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