Diabetes Mellitus Prediction Using Artificial Neural Network
Student: Ayomide Michael Aladetuyi (Project, 2025)
Department of Computer and Information Science
Bamidele Olumilua University of Edu. Science and Tech. Ikere Ekiti, Ekiti State
Abstract
The project addresses the global health concern of diabetes mellitus by creating a predictive model using an Artificial Neural Network (ANN). The model was trained and tested on the "Early-Stage Diabetes Risk Prediction Dataset" from Mendeley, which includes demographic and clinical symptom data. After data preprocessing and an 80-20 train-test split, the developed ANN model achieved a high accuracy of 98%. The project successfully deployed this model into a functional web application using Google Colab and Gradio, showcasing a practical tool for early diabetes risk assessment.
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For the full publication, please contact the author directly at: aladetuyiayosire@gmail.com
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Institutions
- Isa Mustapha Agwai I Polytechnic, Lafia, Nasarawa State 2
- Jigawa State Polytechnic, Dutse, Jigawa State 4
- Joseph Sarwuan Tarka University, Makurdi, Benue State 17
- Kaduna Polytechnic (NCE), Kaduna, Kaduna State 2
- Kaduna Polytechnic, Kaduna 332
- Kaduna Polytechnic, Kaduna , Kaduna State (affl To Fed Univ of Tech, Minna) 6
- Kaduna State College of Education, Gidan-Waya (affliatted To Abu) 2
- Kaduna State University, Kaduna, Kaduna State 247
- Kano State Polytechnic, Kano, Kano State 197
- Kano University of Science and Technology, Wudil, Kano State 6