A Comparative Performance Analysis of Machine Learning Approaches for the Early Prediction of Diabetes Disease

Author:

Mahesh T R1,Vivek V1,Kumar Vinoth V1,Natarajan Rajesh2,Sathya S.2,Kanimozhi S.2

Affiliation:

1. JAIN (Deemed-to-be University),Faculty of Engineering and Technology,Department of Computer Science and Engineering,Bangalore,India

2. University of Applied Science and Technology, Shinas. C. Abdul Hakeem College Of Engineering and Technology Melvisharam,Sultanate of Oman

Publisher

IEEE

Reference22 articles.

1. Fine Tuning Smart Manufacturing Enterprise Systems

2. Low power area efficient adaptive FIR filter for hearing aids using distributed arithmetic architecture

3. A Quantum Approach in LiFi Security using Quantum Key Distribution;vinoth kumar;International Journal of Advanced Science and Technology,2020

4. Intelligent Medical Data Analytics Using Classifiers and Clusters in Machine Learning

5. Hierarchal Trust Certificate Distribution using Distributed CA in MANET;vinoth kumar;International Journal of Innovative Technology and Exploring Engineering,2019

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1. A Comprehensive Study of Deep Learning Techniques to Predict Dissimilar Diseases in Diabetes Mellitus Using IoT;Recent Advances in Computer Science and Communications;2024-06

2. Analysis of Deep Learning and Machine Learning Methods for Breast Cancer Detection;2023 International Conference on Computer Science and Emerging Technologies (CSET);2023-10-10

3. Performance Evaluation and Analysis of Different Association Rule Mining (ARM) Algorithms;Handbook of Research on Advancements in AI and IoT Convergence Technologies;2023-05-19

4. Diabetes Prediction using different Machine Learning Classifiers;2023 2nd International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies (ViTECoN);2023-05-05

5. Efficient Data Preprocessing with Ensemble Machine Learning Technique for the Early Detection of Chronic Kidney Disease;Applied Sciences;2023-02-23

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