Research graph
References from Role of foundation models in data-driven tissue diagnostics. Local targets link to admitted publications; unresolved targets remain external evidence.
PathAlign: A vision-language model for whole slide images in histopathology
2024 · External reference
Unresolved reference
2026 · External reference
Unresolved reference
2025 · External reference
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · 2023 · External reference
Deciphering the morphology of tumor-stromal features in invasive breast cancer using artificial intelligence
10.1016/j.modpat.2023.100254 · 2023 · External reference
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
10.1038/s41551-023-01049-7 · 2023 · External reference
MSAI-path: Predicting microsatellite instability from routine histology slides without reinventing the wheel
10.1016/j.modpat.2025.100932 · 2026 · External reference
Unresolved reference
2025 · External reference
Benchmarking pathology foundation models for predicting microsatellite instability in colorectal cancer histopathology
10.1016/j.compmedimag.2025.102680 · 2026 · External reference
An aggregation of aggregation methods in computational pathology
10.1016/j.media.2023.102885 · 2023 · External reference
Role of AI and digital pathology for colorectal immuno-oncology
10.1038/s41416-022-01986-1 · 2023 · External reference
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study
10.1016/s2589-7500(21)00180-1 · 2021 · External reference
Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study
10.1016/s2589-7500(23)00148-6 · 2023 · External reference
Unresolved reference
2025 · External reference
Unresolved reference
2022 · External reference
A comprehensive evaluation of histopathology foundation models for ovarian cancer subtype classification
10.1038/s41698-025-00799-8 · 2025 · External reference
A clinical benchmark of public self-supervised pathology foundation models
10.1038/s41467-025-58796-1 · 2025 · External reference
Unresolved reference
2024 · External reference
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
10.1038/s41591-019-0508-1 · 2019 · External reference
Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection
10.1038/s41591-025-03780-x · 2025 · External reference
Unresolved reference
2024 · External reference
Benchmarking embedding aggregation methods in computational pathology: A clinical data perspective
2024 · External reference
Scaling vision transformers to gigapixel images via hierarchical self-supervised learning
2022 · External reference
Towards a general-purpose foundation model for computational pathology
10.1038/s41591-024-02857-3 · 2024 · External reference
A simple framework for contrastive learning of visual representations
2020 · External reference
SlideChat: A large vision-language assistant for whole-slide pathology image understanding
2025 · External reference
A multimodal whole-slide foundation model for pathology
10.1038/s41591-025-03982-3 · 2025 · External reference
Unresolved reference
2024 · External reference
An image is worth 16x16 words: Transformers for image recognition at scale
2021 · External reference
PaLM-E: An embodied multimodal language model
2023 · External reference
Unresolved reference
2026 · External reference
Unresolved reference
2023 · External reference
Unresolved reference
2024 · External reference
Foundation models in robotics: Applications, challenges, and the future
10.1177/02783649241281508 · 2025 · External reference
Unresolved reference
2024 · External reference
Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study
10.1136/gutjnl-2023-329512 · 2023 · External reference
HistGen: Histopathology report generation via local-global feature encoding and cross-modal context interaction
2024 · External reference
Towards visual question answering on pathology images
2021 · External reference
A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics
10.1038/s43018-024-00793-2 · 2024 · External reference
PathoDuet: Foundation models for pathological slide analysis of h&e and IHC stains
10.1016/j.media.2024.103289 · 2024 · External reference
A visual-language foundation model for pathology image analysis using medical Twitter
10.1038/s41591-023-02504-3 · 2023 · External reference
HEST-1k: A dataset for spatial transcriptomics and histology image analysis
2024 · External reference
Multistain pretraining for slide representation learning in pathology
2025 · External reference
Cellular community detection for tissue phenotyping in colorectal cancer histology images
10.1016/j.media.2020.101696 · 2020 · External reference
Unresolved reference
External reference
Unresolved reference
2024 · External reference
Benchmarking self-supervised learning on diverse pathology datasets
2023 · External reference
Unresolved reference
2026 · External reference
Training state-of-the-art pathology foundation models with orders of magnitude less data
2025 · External reference
Pan-cancer image-based detection of clinically actionable genetic alterations
10.1038/s43018-020-0087-6 · 2020 · External reference
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
10.1371/journal.pmed.1002730 · 2019 · External reference
Multi-class texture analysis in colorectal cancer histology
10.1038/srep27988 · 2016 · External reference
Towards robust foundation models for digital pathology
10.1038/s41467-026-73923-2 · 2026 · External reference
Unresolved reference
2023 · External reference
Unresolved reference
2023 · External reference
Benchmarking pathology foundation models: Adaptation strategies and scenarios
10.1016/j.compbiomed.2025.110031 · 2025 · External reference
10.1109/cvpr52734.2025.02869
10.1109/cvpr52734.2025.02869 · External reference
Interpretable vision-language survival analysis with ordinal inductive bias for computational pathology
2025 · External reference
Graph foundation models: Concepts, opportunities and challenges
10.1109/tpami.2025.3548729 · 2025 · External reference
A visual-language foundation model for computational pathology
10.1038/s41591-024-02856-4 · 2024 · External reference
A multimodal generative AI copilot for human pathology
10.1038/s41586-024-07618-3 · 2024 · External reference
PathBot: A foundation model for pathological image analysis
10.1109/jbhi.2025.3619967 · 2025 · External reference
Unresolved reference
2025 · External reference
A generalizable pathology foundation model using a unified knowledge distillation pretraining framework
10.1038/s41551-025-01488-4 · 2025 · External reference
Benchmarking histopathology foundation models for ovarian cancer bevacizumab treatment response prediction from whole slide images
10.1007/s12672-025-01973-x · 2025 · External reference
MI-VisionShot: Few-shot adaptation of vision-language models for slide-level classification of histopathological images
2025 · External reference
Unresolved reference
2024 · External reference
Benchmarking foundation models as feature extractors for weakly supervised computational pathology
10.1038/s41551-025-01516-3 · 2026 · External reference
Tissue concepts: Supervised foundation models in computational pathology
10.1016/j.compbiomed.2024.109621 · 2025 · External reference
Pathology foundation models
10.31662/jmaj.2024-0206 · 2025 · External reference
Unresolved reference
2023 · External reference
Unresolved reference
2024 · External reference
Unresolved reference
2026 · External reference
Unresolved reference
2025 · External reference
A guide to artificial intelligence for cancer researchers
10.1038/s41568-024-00694-7 · 2024 · External reference
Learning transferable visual models from natural language supervision
2021 · External reference
Benchmarking, ethical alignment, and evaluation framework for conversational AI: Advancing responsible development of ChatGPT
2023 · External reference
Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides
10.1038/s41467-023-42453-6 · 2023 · External reference
Unresolved reference
2024 · External reference
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
10.1038/s41698-023-00365-0 · 2023 · External reference
Unresolved reference
2025 · External reference
Unresolved reference
2024 · External reference
Unresolved reference
2026 · External reference
Toward expert-level medical question answering with large language models
10.1038/s41591-024-03423-7 · 2025 · External reference
Artificial intelligence for digital and computational pathology
10.1038/s44222-023-00096-8 · 2023 · External reference
PathMMU: A massive multimodal expert-level benchmark for understanding and reasoning in pathology
2024 · External reference
PathGen-1.6M: 1.6 million pathology image-text pairs generation through multi-agent collaboration
2025 · External reference
PathAsst: A generative foundation AI assistant towards artificial general intelligence of pathology
2024 · External reference
DABS: A domain-agnostic benchmark for self-supervised learning
2021 · External reference
Clinical-grade multi-organ pathology report generation for multi-scale whole slide images via a semantically guided medical text foundation model
2024 · External reference
Generating dermatopathology reports from gigapixel whole slide images with HistoGPT
10.1038/s41467-025-60014-x · 2025 · External reference
Unresolved reference
2025 · External reference
Evaluation of performance measures in predictive artificial intelligence models to support medical decisions: overview and guidance
2025 · External reference
A foundation model for clinical-grade computational pathology and rare cancers detection
10.1038/s41591-024-03141-0 · 2024 · External reference
Unresolved reference
2025 · External reference
AI-enabled routine h&e image based prognostic marker for early-stage luminal breast cancer
10.1038/s41698-023-00472-y · 2023 · External reference
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
10.1016/j.media.2022.102645 · 2023 · External reference
Foundation model for predicting prognosis and adjuvant therapy benefit from digital pathology in GI cancers
10.1200/jco-24-01501 · 2025 · External reference
Unresolved reference
2025 · External reference
Transformer-based unsupervised contrastive learning for histopathological image classification
10.1016/j.media.2022.102559 · 2022 · External reference
A pathology foundation model for cancer diagnosis and prognosis prediction
10.1038/s41586-024-07894-z · 2024 · External reference
Unresolved reference
2023 · External reference
A vision–language foundation model for precision oncology
10.1038/s41586-024-08378-w · 2025 · External reference
SimMIM: a simple framework for masked image modeling
2022 · External reference
A whole-slide foundation model for digital pathology from real-world data
10.1038/s41586-024-07441-w · 2024 · External reference
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
10.1016/j.media.2025.103456 · 2025 · External reference
A multimodal knowledge-enhanced whole-slide pathology foundation model
10.1038/s41467-025-66220-x · 2025 · External reference
PathOrchestra: a comprehensive foundation model for computational pathology with over 100 diverse clinical-grade tasks
10.1038/s41746-025-02027-w · 2025 · External reference
Be your own teacher: Improve the performance of convolutional neural networks via self distillation
2019 · External reference
Benchmarking PathCLIP for pathology image analysis
10.1007/s10278-024-01128-4 · 2025 · External reference
AGIEval: A human-centric benchmark for evaluating foundation models
2024 · External reference
Unresolved reference
2024 · External reference
Benchmarking PathCLIP for pathology image analysis
10.1007/s10278-024-01128-4 · ExternalCitation · doi-reference
Benchmarking histopathology foundation models for ovarian cancer bevacizumab treatment response prediction from whole slide images
10.1007/s12672-025-01973-x · ExternalCitation · doi-reference
Tissue concepts: Supervised foundation models in computational pathology
10.1016/j.compbiomed.2024.109621 · ExternalCitation · doi-reference
Benchmarking pathology foundation models: Adaptation strategies and scenarios
10.1016/j.compbiomed.2025.110031 · ExternalCitation · doi-reference
Benchmarking pathology foundation models for predicting microsatellite instability in colorectal cancer histopathology
10.1016/j.compmedimag.2025.102680 · ExternalCitation · doi-reference
Cellular community detection for tissue phenotyping in colorectal cancer histology images
10.1016/j.media.2020.101696 · ExternalCitation · doi-reference
Transformer-based unsupervised contrastive learning for histopathological image classification
10.1016/j.media.2022.102559 · ExternalCitation · doi-reference
RetCCL: Clustering-guided contrastive learning for whole-slide image retrieval
10.1016/j.media.2022.102645 · ExternalCitation · doi-reference
An aggregation of aggregation methods in computational pathology
10.1016/j.media.2023.102885 · ExternalCitation · doi-reference
PathoDuet: Foundation models for pathological slide analysis of h&e and IHC stains
10.1016/j.media.2024.103289 · ExternalCitation · doi-reference
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
10.1016/j.media.2025.103456 · ExternalCitation · doi-reference
Deciphering the morphology of tumor-stromal features in invasive breast cancer using artificial intelligence
10.1016/j.modpat.2023.100254 · ExternalCitation · doi-reference
MSAI-path: Predicting microsatellite instability from routine histology slides without reinventing the wheel
10.1016/j.modpat.2025.100932 · ExternalCitation · doi-reference
Development and validation of a weakly supervised deep learning framework to predict the status of molecular pathways and key mutations in colorectal cancer from routine histology images: a retrospective study
10.1016/s2589-7500(21)00180-1 · ExternalCitation · doi-reference
Development and validation of artificial intelligence-based prescreening of large-bowel biopsies taken in the UK and Portugal: a retrospective cohort study
10.1016/s2589-7500(23)00148-6 · ExternalCitation · doi-reference
Role of AI and digital pathology for colorectal immuno-oncology
10.1038/s41416-022-01986-1 · ExternalCitation · doi-reference
Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides
10.1038/s41467-023-42453-6 · ExternalCitation · doi-reference
A clinical benchmark of public self-supervised pathology foundation models
10.1038/s41467-025-58796-1 · ExternalCitation · doi-reference
Generating dermatopathology reports from gigapixel whole slide images with HistoGPT
10.1038/s41467-025-60014-x · ExternalCitation · doi-reference
A multimodal knowledge-enhanced whole-slide pathology foundation model
10.1038/s41467-025-66220-x · ExternalCitation · doi-reference
Towards robust foundation models for digital pathology
10.1038/s41467-026-73923-2 · ExternalCitation · doi-reference
Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging
10.1038/s41551-023-01049-7 · ExternalCitation · doi-reference
A generalizable pathology foundation model using a unified knowledge distillation pretraining framework
10.1038/s41551-025-01488-4 · ExternalCitation · doi-reference
Benchmarking foundation models as feature extractors for weakly supervised computational pathology
10.1038/s41551-025-01516-3 · ExternalCitation · doi-reference
A guide to artificial intelligence for cancer researchers
10.1038/s41568-024-00694-7 · ExternalCitation · doi-reference
A whole-slide foundation model for digital pathology from real-world data
10.1038/s41586-024-07441-w · ExternalCitation · doi-reference
A multimodal generative AI copilot for human pathology
10.1038/s41586-024-07618-3 · ExternalCitation · doi-reference
A pathology foundation model for cancer diagnosis and prognosis prediction
10.1038/s41586-024-07894-z · ExternalCitation · doi-reference
A vision–language foundation model for precision oncology
10.1038/s41586-024-08378-w · ExternalCitation · doi-reference
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
10.1038/s41591-019-0508-1 · ExternalCitation · doi-reference
A visual-language foundation model for pathology image analysis using medical Twitter
10.1038/s41591-023-02504-3 · ExternalCitation · doi-reference
A visual-language foundation model for computational pathology
10.1038/s41591-024-02856-4 · ExternalCitation · doi-reference
Towards a general-purpose foundation model for computational pathology
10.1038/s41591-024-02857-3 · ExternalCitation · doi-reference
A foundation model for clinical-grade computational pathology and rare cancers detection
10.1038/s41591-024-03141-0 · ExternalCitation · doi-reference
Toward expert-level medical question answering with large language models
10.1038/s41591-024-03423-7 · ExternalCitation · doi-reference
Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection
10.1038/s41591-025-03780-x · ExternalCitation · doi-reference
A multimodal whole-slide foundation model for pathology
10.1038/s41591-025-03982-3 · ExternalCitation · doi-reference
Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology
10.1038/s41698-023-00365-0 · ExternalCitation · doi-reference
AI-enabled routine h&e image based prognostic marker for early-stage luminal breast cancer
10.1038/s41698-023-00472-y · ExternalCitation · doi-reference
A comprehensive evaluation of histopathology foundation models for ovarian cancer subtype classification
10.1038/s41698-025-00799-8 · ExternalCitation · doi-reference
PathOrchestra: a comprehensive foundation model for computational pathology with over 100 diverse clinical-grade tasks
10.1038/s41746-025-02027-w · ExternalCitation · doi-reference
Pan-cancer image-based detection of clinically actionable genetic alterations
10.1038/s43018-020-0087-6 · ExternalCitation · doi-reference
A deep-learning framework to predict cancer treatment response from histopathology images through imputed transcriptomics
10.1038/s43018-024-00793-2 · ExternalCitation · doi-reference
Artificial intelligence for digital and computational pathology
10.1038/s44222-023-00096-8 · ExternalCitation · doi-reference
Multi-class texture analysis in colorectal cancer histology
10.1038/srep27988 · ExternalCitation · doi-reference
10.1109/cvpr52734.2025.02869
10.1109/cvpr52734.2025.02869 · ExternalCitation · doi-reference
PathBot: A foundation model for pathological image analysis
10.1109/jbhi.2025.3619967 · ExternalCitation · doi-reference
Graph foundation models: Concepts, opportunities and challenges
10.1109/tpami.2025.3548729 · ExternalCitation · doi-reference
Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study
10.1136/gutjnl-2023-329512 · ExternalCitation · doi-reference
Foundation models in robotics: Applications, challenges, and the future
10.1177/02783649241281508 · ExternalCitation · doi-reference
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
10.1186/s12909-023-04698-z · ExternalCitation · doi-reference
Foundation model for predicting prognosis and adjuvant therapy benefit from digital pathology in GI cancers
10.1200/jco-24-01501 · ExternalCitation · doi-reference
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
10.1371/journal.pmed.1002730 · ExternalCitation · doi-reference
Pathology foundation models
10.31662/jmaj.2024-0206 · ExternalCitation · doi-reference
