An IOT Based Smart Health Care System using Deep Learning Technique for Diabetes Prediction


  • T.Ramyaveni, V.Maniraj


Diabetes, IoT health care system, deep learning, accuracy


Diabetes is a chronic disorder brought on by a malfunction in the metabolism of carbohydrates, and it has emerged as a major global health issue. But in addition to a review of important symptoms, several time-consuming tests are performed to identify diabetes. Healthcare systems provide specialized services in a variety of fields to help patients integrate into their regular daily activities. The primary goal of this work is to use the Transformer neural network to increase the accuracy of diabetes prediction using an IoT-based healthcare system. The outcomes on the Pima Indian dataset (PID) demonstrate the efficacy of the deep learning approach with prediction accuracy scores of 98.54%, sensitivity levels of 95.36%, specificity levels of 94.52%, and F1 score values of 92.58% for diabetes prediction.


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How to Cite

T.Ramyaveni. (2024). An IOT Based Smart Health Care System using Deep Learning Technique for Diabetes Prediction . International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 2418–2425. Retrieved from



Research Article