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A COMPREHENSIVE REVIEW ON "ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND BIG DATA" IN PHARMACEUTICAL WORLD

Authors: Krishna Prasad Davarasingi*, Lakshmi Prameela Devi Katari;

A COMPREHENSIVE REVIEW ON "ARTIFICIAL INTELLIGENCE, MACHINE LEARNING AND BIG DATA" IN PHARMACEUTICAL WORLD

Abstract

Artificial Intelligence(AI), Machine Learning(ML) and Big Data are facilitating the present society as front runner beneficiary, This review highlights the imactful use of AI, ML and Big Data in diverse areas of pharmaceutical fields. Drug Discovery and development with collaborative inputs of technology reducing the human workload as achieving the target in a short period. This paper surveys big data with highlighting the big data analytics. Big data analytics covers integration and analysis of large amount of complex heterogeneous data such as various – omics data (genomics, epigenomics, transcriptomics, proteomics, metabolomics, interactomics, pharmacogenomics, diseasomics), biomedical data and electronic health records data. We underline the challenging issues about big data privacy and security. Keywords: Artificial Intelligence(AI), Machine Learning(ML) and Big Data, Technology, Big Data Analytics, Data Mining, Health Informatics, Healthcare Information

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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