Development of an AI-Driven Medical Diagnostic System for Type-2 Diabetes Detection

• Author(s): Igwilo Chioma Goodness; Prof V. E Ejiofor; Dr. S. A Alade; Dr. Rose U. Paul
• Paper ID: 1713849
• Page: 2324-2335
• Published Date: 30-01-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 7 January-2026

Abstract

Diabetes is a growing health concern worldwide, and early detection is crucial for effective treatment. This paper introduces a predictive model that combines Support Vector Machine (SVM) and Random Forest algorithms with a soft voting classifier to detect diabetes based on clinical data. The ensemble model leverages the strengths of both SVM and RF to improve overall performance. The methodology follows an Object Oriented Analysis and Design Methodology (OOADM) to model the system architecture and to address class imbalance issues, Synthetic Minority Over-sampling Technique (SMOTE) is employed as a data balancing technique. The proposed approach employs Electronic Health Records (EHR) and a user-friendly interface for efficient data analysis and real-time prediction incorporating attributes such as blood pressure, age, BMI, smoking status, and physical activity to predict diabetes. The results demonstrates the effectiveness of ensemble machine learning in identifying diabetes patients, achieving 96 % of accuracy, 97% of precision, 99% of recall, and 98% of F1-score highlighting its potential for early detection and providing a promising direction for future research and development of robust real-time prediction systems.

Keywords

Diabetes, machine learning, SVM, RF, Electronic Health Records(EHR)

Citations

IRE Journals:
Igwilo Chioma Goodness, Prof V. E Ejiofor, Dr. S. A Alade, Dr. Rose U. Paul "Development of an AI-Driven Medical Diagnostic System for Type-2 Diabetes Detection" Iconic Research And Engineering Journals Volume 9 Issue 7 2026 Page 2324-2335

IEEE:
Igwilo Chioma Goodness, Prof V. E Ejiofor, Dr. S. A Alade, Dr. Rose U. Paul "Development of an AI-Driven Medical Diagnostic System for Type-2 Diabetes Detection" Iconic Research And Engineering Journals, 9(7)