Diabetes Mellitus Type 2 and Prediction Making Use of Big Data and Machine Learning Algorithms

Archana Jain; Suraj Malik; Akshay Raj

Authors

Archana Jain Research Scholar, Department of Computer Science and Engineering, School of Engineering & Technology, IIMT University, India
Suraj Malik Associate Professor, Department of Computer Science and Engineering, School of Engineering & Technology, IIMT University, India
Akshay Raj Assistant Professor, Department of Research & Development, IIMT University, India

Keywords:

Diabetes Mellitus Type 2, Hyperglycaemia, Insulin Resistance, Early Prediction, Disease Prevention, Predictive Modelling, Big Data, Machine Learning

Abstract

In the 21st century, Diabetes Mellitus Type 2 is a major health problem in the world. It occurs due to persistent hyperglycaemia and insulin resistance. If the disease is predicted in its early stages, effective prevention and management can be achieved. In this paper, some current developments in predictive modelling based on Big data and Machine learning algorithms for Diabetes Mellitus Type 2 have been reviewed. It compares and analyses the work of various Machine Learning algorithms, outlines their potential and constraints, and points to their applications and future research in this field. Recent studies (2022-2025) indicate that machine learning and deep learning models are better than traditional statistical models for risk stratification and early prediction. However, there are still issues with data quality, ethics, and model interpretability. The article provides suggestions for further research in the field of ethical Artificial Intelligence, the integration of multimodal data, and its application to real-world practice.

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