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Adversarial Attacks on Medical Image Classification
Min Jen Tsai
*
, Ping Yi Lin, Ming En Lee
*
此作品的通信作者
資訊管理研究所
研究成果
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引文 斯高帕斯（Scopus）
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Keyphrases
Medical Image
100%
Adversarial Attack
100%
Medical Image Classification
100%
Deep Neural Network
66%
Computer-aided Diagnosis (CADx)
66%
Clinical Decisions
33%
Clinical Application
33%
Misclassification
33%
Classification Performance
33%
Classification Robustness
33%
Imaging Techniques
33%
Multi-class
33%
Pixel Level
33%
Radiograph
33%
Number of pixels
33%
Multi-pixel
33%
Inaccurate Predictions
33%
Deep Learning Model
33%
Radiography
33%
Medical Image Data
33%
Multi-label Data
33%
Imaging Facility
33%
Computer Science
Neural Network Model
100%
Deep Neural Network
100%
Image Classification
100%
Aided Diagnosis
100%
Adversarial Machine Learning
100%
Experimental Result
50%
Classification Performance
50%
Clinical Application
50%
Deep Learning Model
50%
Engineering
Medical Image
100%
Image Classification
100%
Network Model
33%
Computer Aided Diagnosis
33%
Deep Neural Network
33%
Misclassification
16%
Experimental Result
16%
Classification Performance
16%
Clinical Application
16%
Pixel Level
16%
Deep Learning Method
16%
Mathematics
Deep Neural Network
100%
Network Model
100%
Clinical Decision
50%
Deep Learning Method
50%
Chemical Engineering
Deep Neural Network
100%
Deep Learning Method
50%