Manuscript Number : IJSRSET207644

Early Detection of Type-2 Diabetes Using Federated Learning

Authors(2) :-M. Lincy, Dr. A. Meena Kowshalya

Data privacy and security are incredibly important in the healthcare industry. Federated learning is a new way of training a machine learning algorithm using distributed data which is not hosted in a centralized server. Numerous centralized machine learning models exists in literature but none offers privacy to users’ data. This paper proposes a federated learning approach for early detection of Type-2 Diabetes among patients. A simple federated architecture is exploited for early detection of Type-2 diabetes. We compare the proposed federated learning model against our centralised approach. Experimental results prove that the federated learning model ensures significant privacy over centralised learning model whereas compromising accuracy for a subtle extend.

Authors and Affiliations

M. Lincy
Department of Computer Science and Engineering, Government College of Technology, Coimbatore, Tamil Nadu, India
Dr. A. Meena Kowshalya
Department of Computer Science and Engineering, Government College of Technology, Coimbatore, Tamil Nadu, India

Federated learning, decentralized model, Differential Privacy, Feature Selection, Type 2 diabetes

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Publication Details

Published in : Volume 7 | Issue 6 | November-December 2020
Date of Publication : 2020-12-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 257-267
Manuscript Number : IJSRSET207644
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

M. Lincy, Dr. A. Meena Kowshalya, " Early Detection of Type-2 Diabetes Using Federated Learning, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 7, Issue 6, pp.257-267, November-December-2020. Available at doi : https://doi.org/10.32628/IJSRSET207644      Journal URL : https://res.ijsrset.com/IJSRSET207644

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