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
- Sokoto State University, Sokoto, Sokoto State 42
- St. Albert The Great Major Seminary, Abeokuta. (affl. To University of Benin) 1
- Sule Lamido University, Kafin Hausa, Jigawa State 4
- Tai Solarin University of Education, Ijagun, Ogun State 18
- Tansian University, Oba, Anambra State 1
- Taraba State University, Jalingo, Taraba State 32
- Temple-Gate Polytechnic, Osisioma, Abia State 1
- The Oke-Ogun Polytechnic, Saki, Oyo State 6
- The Polytechnic, Ibadan, Oyo State 13
- THOMAS ADEWUMI UNIVERSITY, OKO-IRESE, KWARA STATE 1