Dementia Prognostication using Machine Learning
Himanshu Pandey1, Kundan Kishor2, K. C. Prabu Shankar3
1Mr.Himanshu Pandey*, Department of Computer Science and Engineering at Faculty of Engineering and Technology, SRM Institute of Science and Technology (SRM IST), Deemed to be University, Kattankulathur, Chennai, India.
2Mr. Kundan Kishor, Department of Computer Science and Engineering at Faculty of Engineering and Technology, SRM Institute of Science and Technology (SRM IST), Deemed to be University, Kattankulathur, Chennai, India.
3Mr. K. C. Prabu Shankar, Assistant Professor (O.G), Department of Computer Science and Engineering, SRM Institute of Science and Technology (SRM IST), Deemed to be University, Kattankulathur, Chennai, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 29, 2020. | Manuscript published on April 10, 2020. | PP:1199-1203 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3673049620/2020©BEIESP | DOI: 10.35940/ijitee.F3673.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Since the introduction of Machine Learning in the field of disease analysis and diagnosis, it has been revolutionized the industry by a big margin. And as a result, many frameworks for disease prognostics have been developed. This paperfocuses on the analysis of three different machine learning algorithms – Neural network, Naïve bayes and SVM on dementia. While the paper focuses more on comparison of the three algorithms, we also try to find out about the important features and causes related to dementia prognostication. Dementia is a severe neurological disease which renders a person unable to use memory and logic if not treated at the early stage so a correct implementation of fast machine learning algorithm may increase the chances of successful treatment. Analysis of the three algorithms will provide algorithm pathway to do further research and create a more complex system for disease prognostication.
Keywords: Machine Learning, SVM, Neural Network, Dementia, Naïve Bayes
Scope of the Article: Machine Learning