Author(s): Anish Chittora, Mary Mekala A

Email(s): amarymekala@vit.ac.in

DOI: 10.5958/0974-360X.2017.00755.7   

Address: Anish Chittora, Mary Mekala A*
Vellore Institute of Technology, Vellore, India
*Corresponding Author

Published In:   Volume - 10,      Issue - 12,     Year - 2017


ABSTRACT:
Just about two decades before, the dataflow in the pharmaceutical (Medical) business was generally straight forward and the use of technology was limited. In any case, as we advance into a more incorporated world where innovation plays an important part in business forms, the data exchange process has turned out to be more confounded. Today expanding in innovation is utilized to help the pharmaceutical (Medical) firms deal with their inventories and to grow new item and administrations. Compound Informatics is the utilization of Computer and Information Technology, connected to a scope of issues in the field of Chemistry. It changes the information into data and data into learning for the proposed motivation behind settling on better choices speedier in the region of medication ID and advancement. With Data Mining, all through medication disclosure, information is gathered relating concoction structures to each other. The Data Mining Technique "classification Process" partitions the databases of obscure medications in groups in light of their closeness. It makes utilization of Lipinski Rule which characterizes those mixes as Drug like which have properties certain to medication similarity. In this paper, weka tool, R studio as well as java language for classification of data sets is used.


Cite this article:
Anish Chittora, Mary Mekala A. Discovery of Drug and Medicine Using Data Mining Techniques. Research J. Pharm. and Tech 2017; 10(12): 4147-4151. doi: 10.5958/0974-360X.2017.00755.7

Cite(Electronic):
Anish Chittora, Mary Mekala A. Discovery of Drug and Medicine Using Data Mining Techniques. Research J. Pharm. and Tech 2017; 10(12): 4147-4151. doi: 10.5958/0974-360X.2017.00755.7   Available on: https://www.rjptonline.org/AbstractView.aspx?PID=2017-10-12-6


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RNI: CHHENG00387/33/1/2008-TC                     
DOI: 10.5958/0974-360X 

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