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
- Redeemers University, Ede, Osun State 4
- Rhema University, Aba, Abia State 11
- Rivers State University of Science and Technology, Port Harcourt, Rivers State 3
- RIVERS STATE UNIVERSITY, PORT HARCOURT, RIVERS STATE 13
- Rufus Giwa Polytechnic, Owo, Ondo State 2
- Saadatu Rimi College of Edu, Kumbotso, Kano State (affiliated To Abu, Zaria) 1
- Salem University, Lokoja, Kogi State 4
- School of Health Information Mgt (Uch, Ibadan), Oyo State 5
- School of Health Information Mgt, Oau Teaching Hospital, Ile-Ife, Osun State 30
- Skyline University Nigeria, Kano, Kano State 2