Security and Privacy Measures to Protect Machine Learning in Medical Applications-Reference-Cited by-同舟云学术

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Security and Privacy Measures to Protect Machine Learning in Medical Applications

Published:2024-05-09 Issue: Volume:10 Page:641-646
ISSN:
Container-title:2024 International Conference on Communication, Computer Sciences and Engineering (IC3SE)
language:
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Author:

Singh Rashi¹,Ruchika ²,Joshi Jyoti³,Goyal Archna²,Rathi Preeti⁴,Joshi Kireet⁵

Affiliation:

1. School of Engineering & Technology, MVN University,Palwal

2. KR Mangalam University,Department of Computer Science and Engineering

3. Graphic Era Hill University,Computer Science and Engineering,Dehradun,Uttarakhand

4. School of Engineering and Technology

5. Graphic Era Deemed to be University,Computer Science and Engineering,Dehradun,Uttarakhand

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10592860/10592845/10592985.pdf?arnumber=10592985

Reference17 articles.

1. Enhancing healthcare security in the digital era: Safeguarding medical images with lightweight cryptographic techniques in IoT healthcare applications

2. Fed-Inforce-Fusion: A federated reinforcement-based fusion model for security and privacy protection of IoMT networks against cyber-attacks

3. Secure and privacy-preserving automated machine learning operations into end-to-end integrated IoT-edge-artificial intelligence-blockchain monitoring system for diabetes mellitus prediction

4. Deep Learning for the Intersection of Ethics and Privacy in Healthcare

5. Mathematical implementation of fusion of medical images in continuous wavelet domain;Yadav;Journal of Advanced Research in dynamical and control system,2019

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