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Standard Cog Exploration on Medicinal Data

International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 119 - Number 10
Year of Publication: 2015
Vadamodula Prasad
Thamada Srinivasa Rao
Ankit Kumar Surana

Vadamodula Prasad, Thamada Srinivasa Rao and Ankit Kumar Surana. Article: Standard Cog Exploration on Medicinal Data. International Journal of Computer Applications 119(10):34-38, June 2015. Full text available. BibTeX

	author = {Vadamodula Prasad and Thamada Srinivasa Rao and Ankit Kumar Surana},
	title = {Article: Standard Cog Exploration on Medicinal Data},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {119},
	number = {10},
	pages = {34-38},
	month = {June},
	note = {Full text available}


In this paper, we diagnose disease by implementing principal component analysis based on the user entered values for various symptoms. It considers components from the user entered values and compares them with the values in the database. Here the diagnosis is done by the method of prediction using trained data sets (TDS) and the results are compared by using suitable data matching systems (DMS). The TDS are provided by Intelligent System Laboratory of K. N. Toosi University of Technology, Imam Khomeini Hospital. If the user entered symptom values exist in the medical dataset then the percentage of getting an output that is true is 100%, if the symptom values do not exist, then the disease is predicted. PCA provides a precise disease prediction with the disease name and referral source which are optimized and neared to the true value in the datasets. Prediction based on machine learning algorithm gives an output that is 92%. This work predicts the actual levels of thyroid in human body.


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