A detailed investigation in determining Alzheimer’s disease and its risk factor using different classification techniques

Mahendran Radha (1) , Anitha M (2) , Jeyabaskar Suganya (3)
(1) Department of Bioinformatics, School of Life Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamil Nadu, India, India ,
(2) Department of Bioinformatics, School of Life Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamil Nadu, India, India ,
(3) Department of Bioinformatics, School of Life Sciences, Vels Institute of Science, Technology and Advanced Studies (VISTAS), Chennai, Tamil Nadu, India, India

Abstract

The prevalence of genetic disorders has recently crept surprisingly high. Neurodegenerative complications, specifically, pose physical and mental stress to parents and caretakers. These complications may be witnessed in the case  of dementia. The general dementia type that accounted for between 60 to  80 per cent of psychiatric illnesses was Alzheimer’s disease. At an earlier stage, illness detection serves as a critical task that helps the diseased person to enjoy a decent quality of life. It has become a much necessitated strategy towards relying on automated techniques like data mining approach for early diagnosis and assessment of risk factors concerned with Alzheimer’s. There has been an unprecedented growth of interest concerned with devising novelized approaches proposed in recent times for classifying the disease. However, there is still a grave need for developing an efficacious approach for better prognosis and classification. Data mining is carried out using different machine-learning approaches to assess the risk factors for Alzheimer’s disease. Through the present research, and we compared numerous classification methods such as Decision Tree, Linear SVM, KNN, Logistic Regression, Radial SVM, and Random Forest, and finally reported the most outstanding approach in terms of its accuracy.

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Authors

Mahendran Radha
mahenradha@gmail.com (Primary Contact)
Anitha M
Jeyabaskar Suganya
Mahendran Radha, Anitha M, & Jeyabaskar Suganya. (2021). A detailed investigation in determining Alzheimer’s disease and its risk factor using different classification techniques. International Journal of Research in Pharmaceutical Sciences, 12(1), 374–377. Retrieved from https://ijrps.com/home/article/view/254

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