Prediction the best predictor for urea reading among diabetic patients using artificial neural networks (ANNS) models

• Main Authors: Nor Farid Mohd Noor, Wan Muhamad Amir W Ahmad, Mohamad Arif Awang Nawi, Farah Muna Mohamad Ghazali, Nor Azlida Aleng, Ramizu Shaari, Ahmad Mukifza Harun, Razif Abas
• Format: Article
• Language: English; English
• Published: Cancer Research Institute, Sapporo Medical University 2021
• Subjects: QA76.75-76.765 Computer software
• Online Access: https://eprints.ums.edu.my/id/eprint/30309/1/Prediction%20the%20best%20predictor%20for%20urea%20reading%20among%20diabetic%20patients%20using%20artificial%20neural%20networks%20%28ANNS%29%20models%20FULL%20TEXT.pdf; https://eprints.ums.edu.my/id/eprint/30309/3/Prediction%20the%20best%20predictor%20for%20urea%20reading%20among%20diabetic%20patients%20using%20artificial%20neural%20networks%20%28ANNS%29%20models%20ABSTRACT.pdf; https://eprints.ums.edu.my/id/eprint/30309/; https://www.maejournal.com/volume/SMJ/55/01/prediction-the-best-predictor-for-urea-reading-among-diabetic-patients-using-artificial-neural-networks-anns-models-601ac303de7bf.pdf

This study aims to develop the Artificial Neural Network (ANN) through Multilayer Perceptron Neural Network (MLP) by considering the bootstrapping methodology. Applying the bootstrapping approach in MLP methodology improves the precision of the related urea level determination factor. This model dev...