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
- Federal College of Education (Tech), Gusau, (Affl To Abu Zaria), Zamfara State 1
- Federal College of Education, Abeokuta (Aff To University of Ibadan), Ogun State 2
- Federal College of Education, Eha-Amufu, Enugu State 1
- Federal College of Education, Kano (Affl To Ahmadu Bello University, Zaria) 1
- Federal College of Education, Kontagora, (Affl To Abu, Zaria), Niger State 2
- Federal College of Education, Okene, (Affl. To University of Ibadan), Kogi State 3
- Federal College of Education, Pankshin, (Affl To Uni of Jos), Plateau State 2
- Federal College of Education, Zaria, Kaduna State (affl To Abu, Zaria) 1
- Federal College of Wildlife Management, New Bussa, Niger State 1
- Federal Cooperative College, Ibadan P.m.b. 5033, Eleyele, Ibadan, Oyo State 3