Integration of nested cross-validation, automated hyperparameter optimization, high-performance computing to reduce and quantify the variance of test performance estimation of deep learning models
PositiveArtificial Intelligence
- The introduction of NACHOS aims to reduce and quantify the variance in test performance metrics of deep learning models, addressing the biases in their real
- This development is significant as it enhances the trustworthiness of deep learning models in medical imaging, which is crucial for their deployment in clinical settings.
- The integration of high
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