Diabetes Prediction using Deep Learning

Author Name : S. Haripriya, S. Lehitha, A. Rajesh, K. Rajeshwar Rao, S. L. Srikar, Thayyaba Khatoon

DOI: https://doi.org/10.56025/IJARESM.2023.116231485

ABSTRACT

Deep learning approaches are used to predict diabetes accurately as humans do. In this paper, keras in which it is an neural network classifier, an unsupervised learning approach is used for prediction on Pima Indian Diabetes dataset. The prevalence of diabetes is projected to continue rising, highlighting the urgent need for effective prevention and management strategies. Machine learning techniques, including deep learning, have been increasingly used in healthcare to analyze large datasets and develop predictive models for disease diagnosis and management. The proposed model offers a potential tool for healthcare providers to identify patients at high risk of developing diabetes and take preventive measures. In addition, the proposed deep learning model offers several advantages over traditional statistical methods. It can learn from large datasets and identify complex patterns that may be missed by traditional statistical approaches.

Keywords: Neural Networks, Keras, Deep Learning for Predicting Diabetes (DLPD), PIMA INDIAN dataset.