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.
Keywords
For the full publication, please contact the author directly at: aladetuyiayosire@gmail.com
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Institutions
- Binyaminu Usman Polytechnic, Hadijia, Jigawa State 3
- Borno State University, Maiduguri, Borno State 15
- Bowen University, Iwo, Osun State 1
- Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State 255
- College of Agriculture and Animal Science, Mando Road, Kaduna, Kaduna State 1
- College of Agriculture, Science and Technology, Lafia, Nasarawa State 8
- College of Education, Akwanga (affl To Ahmadu Bello Univ, Zaria) 1
- College of Education, Eha Amufu, (Affliliated To Unn), Enugu State 1
- College of Education, Warri (Affiliated To Delta State Uni, Abraka), Delta State 1
- College of Health Technology, Calabar, Cross River State 1