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Found 6 papers, 2 papers with code
Generalisation effects of predictive uncertainty estimation in deep learning for digital pathology
In this work we evaluate if adding uncertainty estimates for DL predictions in digital pathology could result in increased value for the clinical applications, by boosting the general predictive performance or by detecting mispredictions.
Learning Representations with Contrastive Self-Supervised Learning for Histopathology Applications
We bring forward a number of considerations, such as view generation for the contrastive objective and hyper-parameter tuning.
Ensembles of GANs for synthetic training data generation
This work investigates the use of synthetic images, created by generative adversarial networks (GANs), as the only source of training data.
Unsupervised anomaly detection in digital pathology using GANs
Machine learning (ML) algorithms are optimized for the distribution represented by the training data.
Survey of XAI in digital pathology
We present a survey on XAI within digital pathology, a medical imaging sub-discipline with particular characteristics and needs.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
A Closer Look at Domain Shift for Deep Learning in Histopathology
Most centrally, we present a novel measure for evaluating the distance between domains in the context of the learned representation of a particular model.
