Advancing diagnostic performance and clinical usability of neural networks via adversarial training and dual batch normalization.
Tianyu HanSven NebelungFederico PedersoliMarkus ZimmermannMaximilian Schulze-HagenMichael HoChristoph HaarburgerFabian KiesslingChristiane KuhlVolkmar SchulzDaniel TruhnPublished in: CoRR (2020)
Keyphrases
- neural network
- training process
- training algorithm
- diagnostic imaging
- disease diagnosis
- back propagation
- backpropagation algorithm
- medical diagnostic
- clinical setting
- feedforward neural networks
- feed forward neural networks
- multi layer perceptron
- pattern recognition
- recurrent networks
- neural network training
- clinical diagnosis
- neural network model
- clinically relevant
- medical students
- computer aided diagnosis systems
- acute myocardial infarction
- batch mode
- diagnostic tests
- expert systems
- recurrent neural networks
- artificial neural networks
- clinical trials
- genetic algorithm
- error back propagation
- differential diagnosis
- neural network structure
- online learning
- fuzzy logic
- training examples
- diagnostic process
- fault diagnosis
- clinical decision support systems
- preprocessing
- decision making
- diagnostic reasoning