Privacy Preserving Data Mining Framework for Negative Association Rules: An Application to Healthcare Informatics-Reference-Cited by-同舟云学术

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Privacy Preserving Data Mining Framework for Negative Association Rules: An Application to Healthcare Informatics

Published:2022 Issue: Volume:10 Page:76268-76280
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Darwish Saad M.¹^ORCID,Essa Reham M.²,Osman Mohamed A.²,Ismail Ahmed A.³

Affiliation:

1. Department of Information Technology, Institute of Graduate Studies and Research, University of Alexandria, Alexandria, Egypt

2. Department of Information System, Higher Institute for Management and Information Technology, Kafr El-Sheikh, Egypt

3. Higher Institute of Computers and Information Systems, Abo Qir, Alexandria, Egypt

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09832893.pdf?arnumber=9832893

Reference64 articles.

1. Privacy-Preserving Data Mining in Spatiotemporal Databases Based on Mining Negative Association Rules

2. A Survey on Privacy Properties for Data Publishing of Relational Data

3. An overview of privacy preserving data mining;divanis;ACM Mag Students,2009

4. A Grid-Based Swarm Intelligence Algorithm for Privacy-Preserving Data Mining

5. Ant Colony System Sanitization Approach to Hiding Sensitive Itemsets

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2. Securing Sensitive Medical Information with Basic and Pre-large Coati Optimization Algorithm for E-Health System Data Sanitation;Wireless Personal Communications;2024-05

3. Privacy‐preserving credit risk analysis based on homomorphic encryption aware logistic regression in the cloud;SECURITY AND PRIVACY;2024-01-28

4. Preserving Privacy in Association Rule Mining Using Metaheuristic-Based Algorithms: A Systematic Literature Review;IEEE Access;2024

5. Integrated approach for healthcare data protection and security: A survey;AIP Conference Proceedings;2024

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