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Artificial Intelligent Based Predictive Tool for Diabetes Prevention Management

Kala H.*, Nithya Rani N.**, Kaviya K.***, Priyanka K.****, Pavithra R.*****

*,***-***** Department of Biomedical Engineering, Mahendra College of Engineering, Salem, Tamil Nadu, India.

** Department of Electronics & Instrumentation Engineering, Sri Sairam Engineering College, Chennai, Tamil Nadu, India.

Periodicity:July - December'2025

Abstract

The global incidence of Diabetes mellitus is on the rise, leading to significant health challenges by increasing the pressure on healthcare systems. To enhance patient lower complications, early prevention is essential. This paper discusses the validation of an artificial intelligence (AI) prediction tool designed to identify individuals at a sensitive risk of diabetes. Advanced machine learning algorithms like random forest and support vector machine are used in this research, and neural networks are used to identify the patterns and relationships of diabetes onset, utilizing a comprehensive dataset that encompasses demographic, clinical, and elements from specific data sources such as electronic records and population surveys. Feature selection was implemented to improve the model's clarity and effectiveness.

Keywords

Healthcare Technology, Predictive Analytics, Diabetes Prediction, Machine Learning, Artificial Intelligence.

How to Cite this Article?

Kala, H., Rani, N. N., Kaviya, K., Priyanka, K., and Pavithra, R. (2025). Artificial Intelligent Based Predictive Tool for Diabetes Prevention Management. i-manager’s Journal on Artificial Intelligence & Machine Learning, 3(2), 45-54.

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Artificial Intelligent Based Predictive Tool for Diabetes Prevention Management

Abstract

Keywords

How to Cite this Article?

References

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