Validate the factor from multiple logistic regression using artificial neural networks (ANNS) model: a case study of an elderly health status at receiving home care

Mohamad Ghazali, Farah Muna and Wan Ahmad, Wan Muhamad Amir and Awang Nawi, Mohamad Arif and Mohd Ibrahim, Mohamad Shafiq (2020) Validate the factor from multiple logistic regression using artificial neural networks (ANNS) model: a case study of an elderly health status at receiving home care. Sapporo Medical Journal, 54 (10). pp. 1-11. ISSN 0036-472X

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Abstract

This study aims to validate the factor that perhaps influences the health status of an elderly at receiving home care. This research paper, we developed the R syntax for Multilayer Perceptron Neural Network (MLPNN) which considering the logistic based selection. At first, the related factors will be determined through multiple logistics regression procedures, then the selected variable will be validate using Artificial Neural Networks (ANNS) through the Multilayer Perceptron Neural Network (MLPNN). The validation process will be emphasizing on the Mean Square Error for forecasting (MSE-F) and the accuracy value. Through this developed methodology, we hope that the significant variable which treated as input to MLPNN will lower the MSE-F.Health. Through the developed MLPNN methodology, it was found that the Mean Square Error for forecasting (MSE-F.Health) is 0.105 with an accuracy of 91.28%. In conclusion, this showed that the developed model can predict the outcome by more than 90%. The developed R syntax is given in this paper for a better illustration.

Item Type:	Article (Journal)
Additional Information:	8915/86022
Uncontrolled Keywords:	Multilayer perceptron neural network (MLP), Mean square error for forecasting (MSE-F)
Subjects:	Q Science > QA Mathematics
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Dentistry Kulliyyah of Dentistry > Department of Paediatric Dentistry and Dental Public Health
Depositing User:	Dr Mohamad Shafiq Mohd Ibrahim
Date Deposited:	16 Dec 2020 10:12
Last Modified:	07 Apr 2021 09:13
URI:	http://irep.iium.edu.my/id/eprint/86022

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