Multimodal Whole Slide Foundation Model for Pathology

[CVPR 2023] Learning Visual Representations via Language-Guided Sampling

MADELEINE: multi-stain slide representation learning (ECCV'24)

Multimodal prototyping for cancer survival prediction - ICML 2024

HEST: Bringing Spatial Transcriptomics and Histopathology together - NeurIPS 2024 (Spotlight)

Transcriptomics-guided Slide Representation Learning in Computational Pathology - CVPR 2024

Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology - CVPR 2024

Towards a general-purpose foundation model for computational pathology - Nature Medicine

A vision-language foundation model for computational pathology - Nature Medicine

A repository of links with advice related to grad school applications, research, phd etc

Optimize React performance and make your React 70% faster in minutes, not months.

AI-based pathology predicts origins for cancers of unknown primary - Nature

Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images - CVPR 2023

Modeling Dense Multimodal Interactions Between Biological Pathways and Histology for Survival Prediction - CVPR 2024

Machine learning for Analysis of Proteomics in Spatial biology - Nature Communications

Deep learning-based multimodal integration of histology and genomics to improves cancer origin prediction

Multimodal AI for Renal Allograft Biopsy Assessment

[NeurIPS 2023, ICMI 2023] Quantifying & Modeling Multimodal Interactions

[ICLR 2023 spotlight] MEDFAIR: Benchmarking Fairness for Medical Imaging

Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering

Variance pooling to incorporate ITH in CPath models - MICCAI 2022

First commit

ZoomMIL is a multiple instance learning (MIL) method that learns to perform multi-level zooming for efficient Whole-Slide Image (WSI) classification.

Hierarchical Image Pyramid Transformer - CVPR 2022 (Oral)

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)

Code for replicating results presented in the paper: "Quantifying Explainers of Graph Neural Networks in Computational Pathology"

A standardized Python API with necessary preprocessing, machine learning and explainability tools to facilitate graph-analytics in computational pathology.