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Automatic Classification of Medical Data using Machine Learning

Author(s):

Shraddha Bhole , NDMVP's KBTCOE, Nashik; Yogita Bachhav, NDMVP's KBTCOE, Nashik; Tejaswini Patil, NDMVP's KBTCOE, Nashik; Snehal Bedase, NDMVP's KBTCOE, Nashik

Keywords:

Ontology-based classification, Genetics-based classification, Data mining from medical data

Abstract

It is evident that usage of machine learning methods in disease diagnosis has been increasing gradually. In this study, we will detect disease like Diabetes using ontology and genetic based machine learning approach. The first is an ontology-based classification that can directly incorporate human knowledge, while the second is genetic-based data mining algorithm that learns or extracts the domain knowledge from medical data in implicit form. The ontological modeling describes the relationship between classes and individuals. The Genetic-based data mining algorithm is a combination of genetic algorithm and machine learning tools for supervised learning which implement different classifiers. It is useful for analyzing the Diabetes disease with the help of symptoms. It is also better to suggest what kind of precautions the patient should take. In this way, these methodologies can be applied to help patients, students and physicians to decide the disease diabetes the patient has, what is the stage of disease and how it can be treated.

Other Details

Paper ID: IJSRDV4I20391
Published in: Volume : 4, Issue : 2
Publication Date: 01/05/2016
Page(s): 792-793

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