Virchow: A million-slide digital pathology foundation model
Computational pathology uses artificial intelligence to enable precision medicine and
decision support systems through the analysis of whole slide images. It has the potential to …
decision support systems through the analysis of whole slide images. It has the potential to …
Pathoduet: Foundation models for pathological slide analysis of H&E and IHC stains
Large amounts of digitized histopathological data display a promising future for developing
pathological foundation models via self-supervised learning methods. Foundation models …
pathological foundation models via self-supervised learning methods. Foundation models …
[PDF][PDF] A good feature extractor is all you need for weakly supervised learning in histopathology
Deep learning is revolutionising pathology, offering novel opportunities in disease prognosis
and personalised treatment. Historically, stain normalisation has been a crucial …
and personalised treatment. Historically, stain normalisation has been a crucial …
ViTally Consistent: Scaling Biological Representation Learning for Cell Microscopy
K Kenyon-Dean, ZJ Wang, J Urbanik… - arXiv preprint arXiv …, 2024 - arxiv.org
Large-scale cell microscopy screens are used in drug discovery and molecular biology
research to study the effects of millions of chemical and genetic perturbations on cells. To …
research to study the effects of millions of chemical and genetic perturbations on cells. To …
Contrastive-Based Deep Embeddings for Label Noise-Resilient Histopathology Image Classification
L Dedieu, N Nerrienet, A Nivaggioli, C Simmat… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advancements in deep learning have proven highly effective in medical image
classification, notably within histopathology. However, noisy labels represent a critical …
classification, notably within histopathology. However, noisy labels represent a critical …
Going Beyond Salience: Deep Learning for the Discovery of Meaningful Pathomic Markers
GB Machiraju - 2024 - search.proquest.com
Deep learning methods have demonstrated impressive performance in using histopathology
data for both diagnosis and prognosis, sometimes even achieving AUROCs nearly 1.0 …
data for both diagnosis and prognosis, sometimes even achieving AUROCs nearly 1.0 …