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Found 5 papers, 1 papers with code
Evaluation of 3D GANs for Lung Tissue Modelling in Pulmonary CT
This makes high-quality GANs useful for unsupervised anomaly detection in medical imaging.
Is MC Dropout Bayesian?
We question the properties of MC Dropout for approximate inference, as in fact MC Dropout changes the Bayesian model; its predictive posterior assigns $0$ probability to the true model on closed-form benchmarks; the multimodality of its predictive posterior is not a property of the true predictive posterior but a design artefact.
The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification
Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published results.
The Effect of the Loss on Generalization: Empirical Study on Synthetic Lung Nodule Data
Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging.
Bayesian analysis of the prevalence bias: learning and predicting from imbalanced data
This mismatch is known as sampling bias.
