Deep Learning Techniques for the Prediction of Diabetes: A Review

Sunit Kumar Mishra, Arvind Kumar Tiwari

2021

Abstract

Diabetes is a very common disease in the world. If diabetes is detected in early stage, it can be cured easily. Several machine learning techniques are available to predict diabetes in earlier stage using data set. This paper presents review of several machine learning based methods to predict diabetes. This paper provides the comparative analysis of Naive Bayes, ANN, SVM, KNN, Random Forest, LSTM, CNN, BLSTM, ensemble of CNN and LSTM and ensemble of CNN and BLSTM to predict diabetes by taking a dataset.

Paper Citation

in Harvard Style

Mishra S. and Tiwari A. (2021). Deep Learning Techniques for the Prediction of Diabetes: A Review. In Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE, ISBN 978-989-758-544-9, pages 232-237. DOI: 10.5220/0010567400003161

in Bibtex Style

@conference{icacse21,
author={Sunit Kumar Mishra and Arvind Kumar Tiwari},
title={Deep Learning Techniques for the Prediction of Diabetes: A Review},
booktitle={Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,},
year={2021},
pages={232-237},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010567400003161},
isbn={978-989-758-544-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Advanced Computing and Software Engineering - Volume 1: ICACSE,
TI - Deep Learning Techniques for the Prediction of Diabetes: A Review
SN - 978-989-758-544-9
AU - Mishra S.
AU - Tiwari A.
PY - 2021
SP - 232
EP - 237
DO - 10.5220/0010567400003161