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
- Mohammed Lawan College of Agriculture, Maiduguri, Borno State 12
- Moshood Abiola Polytechnic, Abeokuta, Ogun State 7
- Nasarawa State University, Keffi, Nasarawa State 8
- Niger Delta University, Wilberforce Island, Bayelsa State 28
- Niger State College of Education, Minna, (Affl To Usmanu Danfodiyo Uni, Sokoto) 1
- Nigeria Maritime University, Okerenkoko, Delta State 1
- Nigerian Army University, Biu, Borno State 3
- Nile University of Nigeria, Abuja 3
- Nnamdi Azikiwe University, Awka, Anambra State 98
- Northwest University, Kano, Kano State 179