Real-time Monitoring and Early Detection of Diabetes with Bioactive and Biological Impedance Sensors using Hybrid Machine Learning Algorithm-Reference-Cited by-同舟云学术

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Real-time Monitoring and Early Detection of Diabetes with Bioactive and Biological Impedance Sensors using Hybrid Machine Learning Algorithm

Published:2023-05-26 Issue: Volume: Page:
ISSN:
Container-title:2023 4th International Conference for Emerging Technology (INCET)
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Author:

Hariharan S. Dhanush¹,Sridharan Deveshwaran¹,R Kalaiyarasi²,T A Mohanaprakash³,Tamilselvi C.⁴,Sam Dahlia⁴

Affiliation:

1. Panimalar Engineering College,Department of Artificial Intelligence and Data Science,Chennai,India

2. Rajalakshmi Institue of Technology,Department of Artificial Intelligence and Data Science,Chennai,India

3. Panimalar Engineeering College,Department of CSE,Chennai,India

4. Dr. M.G.R Educational and Research Institute,Department of IT,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10169136/10169900/10170610.pdf?arnumber=10170610

Reference15 articles.

1. Diagnosis of Diabetes using computer methods: soft computing methods for diabetes detection using iris;samant,2017

2. Prediction of severity of diabetes mellitus using fuzzy cognitive maps;bhatia;Advances in Life Science and Technology,2015

3. Type 2 diabetes mellitus prediction model based on data mining;wu;Informatics in Medicine Unlocked,2018

4. Prediction of Diabetes using Classification Algorithms

5. Diabetes detection using deep learning algorithms;swapna;ICT Express,2018

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