12 citations · 48 across the 21 of their papers we have counts for
3 papers · 1 filter
Beyond Classification: Pathology Foundation Models as Detection Encoders for Mitotic Figures
Sweta Banerjee, Alireza Teimoury, Nils Porsche +11
Pathology foundation models (FMs) are models trained on vast amounts of typically unlabeled data and have been shown to yield regularized latent spaces that can be used effectively…
Performance evaluation of deep learning models for image analysis: considerations for visual control and statistical metrics
Christof A. Bertram, Jonas Ammeling, Alexander Bartel +2
Deep learning-based automated image analysis (DL-AIA) has been shown to outperform trained pathologists in tasks related to feature quantification. Related to these capacities the…
Stuck on Suggestions: Automation Bias, the Anchoring Effect, and the Factors That Shape Them in Computational Pathology
Emely Rosbach, Jonas Ammeling, Jonathan Ganz +4
Artificial intelligence (AI)-driven decision support systems can improve diagnostic accuracy and efficiency in computational pathology. However, collaboration between human experts…