Structured Medical Pathology Data Hiding Information Association Mining Algorithm Based on Optimized Convolutional Neural Network
When using traditional algorithms to mine the association of hiding information in medical pathological data, there are some problems, such as low recognition rate of association and poor accuracy of mining results. Therefore, structured medical pathology data hiding information association mining a...
Main Authors: | Xiaofeng Li, Yanwei Wang, Gang Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8935218/ |
Similar Items
-
Introducing an algorithm for use to hide sensitive association rules through perturb technique
by: M. Sakenian Dehkordi, et al.
Published: (2016-07-01) -
Efficient Association Rules Hiding Using Genetic Algorithms
by: Naadiya Khuda Bux, et al.
Published: (2018-11-01) -
Integrated Association Rules Complete Hiding Algorithms
by: Mohamed Refaat Abdellah, et al.
Published: (2017-01-01) -
EMOSS: An Efficient Algorithm to Hide Sequential Patterns
by: Olya Sadat Behbahani, et al.
Published: (2015-12-01) -
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
by: Inas Ali Abdulmunem, et al.
Published: (2021-12-01)