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
Filters
Institutions
- Kebbi State University of Science and Technology, Aliero, Kebbi State 6
- Kenule Benson Saro-Wiwa Polytechnic, Bori, Rivers State 18
- Kogi State Polytechnic, Lokoja, Kogi State 4
- Kogi State University, Anyigba 2
- Kwara State College of Health Technology, offa, Kwara State 9
- Kwara State Polytechnic, Ilorin, Kwara State 20
- Kwara State University, Malete, Ilorin, Kwara State 13
- Ladoke Akintola University of Technology, Ogbomoso, Oyo State 39
- Lagos State Poly, Ikorodu, Lagos State 2
- Lagos State University, Ojo, Lagos State 8