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
- UMA UKPAI SCHOOL OF THEOLOGY, UYO, AKWA IBOM STATE (AFFL TO UNIVERSITY OF UYO) 1
- Umaru Ali Shinkafi Polytechnic, Sokoto, Sokoto State 24
- Umaru Musa Yaradua University, Katsina, Katsina State 28
- Umca, Ilorin (Affiliated To University of Ibadan), Kwara State 1
- University of Abuja, Abuja, Fct 117
- University of Africa, Toru-Orua, Bayelsa State 4
- University of Benin, Benin City, Edo State 362
- University of Calabar Teaching Hospital School of Health Information Mgt. 1
- University of Calabar, Calabar, Cross River State 240
- University of Ibadan, Ibadan, Oyo State 14