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International Journal of Scientific Development and Research - IJSDR
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Paper Title: Diagnose Most Desirable Treatment For Disease Using Machine Learning Approach In Relation To Short Text
Authors Name: Vijay Shrikisan Ingle , Amit Mishra , Dr. Shiv K Sahu
Unique Id: IJSDR1604021
Published In: Volume 1 Issue 4, April-2016
Abstract: This paper describe the Machine Learning techniques which is used to construct a computer system that can obey and learn from their experience. Machine learning can easily adapt into the healthcare analysis system in order to acquire perfect and best results. So using machine learning approach existing system able to identify a disease and discover the relevant treatment but it lagging to discover best treatment out of extracting treatments. The proposed system discover meaningful informative sentences from abstracts of published articles from MEDLINE. The MEDLINE contains information about disease and its treatment. The formal goal of a system is to discover a disease and treatment related information and also identify most desirable treatment out of the treatment extracted as a result by merging a computer system into healthcare domain. So the most desirable result will help to doctors in their decision making. The task of discovering best treatment from several treatments found for a given disease is done by using data mining techniques and by forecasting the views of different doctors by using voting system. In order to develop a system that can perfectly discover a disease and most desirable treatment that is reliable and capable for use in commercial healthcare recommender system and electronic Health record system
Keywords: Medline; Healthcare; Voting Algorithm; Electronic Health Record system; Desease & Treatement relation
Cite Article: "Diagnose Most Desirable Treatment For Disease Using Machine Learning Approach In Relation To Short Text", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 4, page no.106 - 111, April-2016, Available :http://www.ijsdr.org/papers/IJSDR1604021.pdf
Downloads: 0001960
Publication Details: Published Paper ID: IJSDR1604021
Registration ID:160129
Published In: Volume 1 Issue 4, April-2016
DOI (Digital Object Identifier):
Page No: 106 - 111
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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