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Development of a Hybrid Dynamic Expert System for the Diagnosis of Peripheral Diabetes and Remedies using a Rule-Based Machine Learning Technique

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Development of a Hybrid Dynamic Expert System for the Diagnosis of Peripheral Diabetes and Remedies using a Rule-Based Machine Learning Technique


Omeye Emmanuel C. | Ngene John N. | Dr. Anyaragbu Hope U. | Dr. Ozioko Ekene | Dr. Iloka Bethram C. | Prof. Inyiama Hycent C.



Omeye Emmanuel C. | Ngene John N. | Dr. Anyaragbu Hope U. | Dr. Ozioko Ekene | Dr. Iloka Bethram C. | Prof. Inyiama Hycent C. "Development of a Hybrid Dynamic Expert System for the Diagnosis of Peripheral Diabetes and Remedies using a Rule-Based Machine Learning Technique" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-7, December 2022, pp.429-438, URL: https://www.ijtsrd.com/papers/ijtsrd52356.pdf

This paper presents the development of a hybrid dynamic expert system for the diagnosis of peripheral diabetes and remedies using a rule-based machine learning technique. The aim was to develop a solution to the risk factors of peripheral diabetes. The methodology applied in this study is the experimental method, and the software design methodology used was the agile methodology. Data was collected from Nnamdi Azikiwe University Teaching Hospitals (NAUTH) and the Lagos State University Teaching Hospital (LASUTH) for patients between the ages of 28-87years suffering from peripheral neuropathy. Other methods used were data integration by applying uniform data access (UDA) technique, data processing using Infinite Impulse Response Filter (IIRF), data extraction with a computerized approach, machine learning algorithm with Dynamic Feed Forward Neural Network (DFNN), rule-base algorithm. The modeling of the hybrid dynamic expert system and remedies was achieved using the DFNN for the detection of DPN and a rule-based model for remedies and recommendations. The models were implemented with MATLAB and Java programming languages. The result when evaluated achieved a Mean Square Error (MSE) of 4.9392e-11 and Regression (R) of 0.99823. The implication of the result showed that the peripheral diabetes detection model correctly learns the peripheral diabetes attributes and was also able to correctly detect peripheral diabetes in patients. The model when compared with other sophisticated models also showed that it achieved a better regression score. The reason was due to the appropriate steps used in the data preparation such as integration and the use of IIFR filter, feature extraction, and the deep configuration of the regression model.

Expert System; Peripheral Diabetes; Neural Network; Machine Learning, MSE, R


IJTSRD52356
Volume-6 | Issue-7, December 2022
429-438
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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