Journal Paper

Paper Title - Identifying Best Treatment For Disease Using Machine Learning Approach In Relation To Short Text


Abstract
The goal of machine learning is to build computer systems that can adapt and learn from their experience. Machine learning helps to integrate the computer system into the healthcare field in order to obtain accurate and best results. Here the system deals with automatic identification of informative sentences from abstracts of published articles by MEDLINE. The main aim here is to integrate the computer based systems into healthcare fields and build an application that is capable of automatically identifying and disseminating disease and treatment related information, further it also identifies the best treatment out of the treatment obtained as a results and providing a helping hand to the doctors in their decision making. The task of identifying best treatment from the multiple treatments found for a given disease is done by using data mining techniques and by calculating the views of different doctors recommending those treatments by using voting method in the system. In Future the proposed system can also be integrated in an application to be used in the medical care domain. The framework’s designed is reliable and capable for use in commercial recommender system and it can be integrated in a new Electronic Health Record system


Author - Bharti E. Nerkar, Sanjay S. Gharde

Citation - Bharti E. Nerkar   ,   Sanjay S. Gharde   ,   Bharti E. Nerkar, Sanjay S. Gharde " Identifying Best Treatment For Disease Using Machine Learning Approach In Relation To Short Text " , International Journal of Industrial Electronics and Electrical Engineering , Volume-2,Issue-1  ( Jan, 2014 )

Indexed - Google Scholar


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| Published on 2014-06-16