mlsanityData to 14 Oct 2026

Artificial Intelligence for Digital and Computational Pathology

arXiv 2401.06148 ↗First posted 13 Dec 2023eess.IV cs.AI cs.CVcited by 108

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Abstract (arXiv)

Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence, including deep learning, have boosted the field of computational pathology. This field holds tremendous potential to automate clinical diagnosis, predict patient prognosis and response to therapy, and discover new morphological biomarkers from tissue images. Some of these artificial intelligence-based systems are now getting approved to assist clinical diagnosis; however, technical barriers remain for their widespread clinical adoption and integration as a research tool. This Review consolidates recent methodological advances in computational pathology for predicting clinical end points in whole-slide images and highlights how these developments enable the automation of clinical practice and the discovery of new biomarkers. We then provide future perspectives as the field expands into a broader range of clinical and research tasks with increasingly diverse modalities of clinical data.

Key facts. Cited by 108 papers in the map (data through 14 Oct 2026). Builds on 67 of its 248 references that are in the map. First posted on arXiv 13 Dec 2023.

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67 of 248 references.

References · 67

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38 more
  1. 2018Continual Lifelong Learning with Neural Networks: A Reviewcited by 1,330
  2. 2018Attention-based Deep Multiple Instance Learningcited by 1,095
  3. 2020Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Imagescited by 745
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  16. 2018BACH: Grand Challenge on Breast Cancer Histology Imagescited by 131
  17. 2021Whole Slide Images are 2D Point Clouds: Context-Aware Survival Prediction using Patch-based Graph Convolutional Networkscited by 124
  18. 2020Deep Learning-based Computational Pathology Predicts Origins for Cancers of Unknown Primarycited by 89
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  24. 2021Hierarchical Graph Representations in Digital Pathologycited by 59
  25. 2022Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathologycited by 58
  26. 2018Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networkscited by 57
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50 most cited of 67 All 67 (JSON)

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 37; 2025: 48; 2026: 23.

108 papers.

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  1. 2024HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysiscited by 107
  2. 2024Phikon-v2, A large and public feature extractor for biomarker predictioncited by 74
  3. 2024Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathologycited by 72
  4. 2024Feature Re-Embedding: Towards Foundation Model-Level Performance in Computational Pathologycited by 67
  5. 2024SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understandingcited by 57
  6. 2024Transcriptomics-guided Slide Representation Learning in Computational Pathologycited by 51
  7. 2024Multimodal Prototyping for cancer survival predictioncited by 47
  8. 2025Distilling foundation models for robust and efficient models in digital pathologycited by 36
  9. 2025Do Multiple Instance Learning Models Transfer?cited by 29
  10. 2024Multistain Pretraining for Slide Representation Learning in Pathologycited by 28
  11. 2025ViLa-MIL: Dual-scale Vision-Language Multiple Instance Learning for Whole Slide Image Classificationcited by 28
  12. 2025Evidence-based diagnostic reasoning with multi-agent copilot for human pathologycited by 27
38 more
  1. 2025PathBench: A comprehensive comparison benchmark for pathology foundation models towards precision oncologycited by 24
  2. 2024Interpretable Vision-Language Survival Analysis with Ordinal Inductive Bias for Computational Pathologycited by 14
  3. 2024A Comprehensive Evaluation of Histopathology Foundation Models for Ovarian Cancer Subtype Classificationcited by 13
  4. 2024Pathology-knowledge Enhanced Multi-instance Prompt Learning for Few-shot Whole Slide Image Classificationcited by 13
  5. 2024MamMIL: Multiple Instance Learning for Whole Slide Images with State Space Modelscited by 12
  6. 2024MPCODER: Multi-user Personalized Code Generator with Explicit and Implicit Style Representation Learningcited by 12
  7. 2024Agent Aggregator with Mask Denoise Mechanism for Histopathology Whole Slide Image Analysiscited by 11
  8. 2024AEM: Attention Entropy Maximization for Multiple Instance Learning based Whole Slide Image Classificationcited by 10
  9. 2024Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data Perspectivecited by 10
  10. 2024Sm: enhanced localization in Multiple Instance Learning for medical imaging classificationcited by 10
  11. 2024Queryable Prototype Multiple Instance Learning with Vision-Language Models for Incremental Whole Slide Image Classificationcited by 10
  12. 2024A New Era in Computational Pathology: A Survey on Foundation and Vision-Language Modelscited by 9
  13. 2025PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Imagescited by 9
  14. 2026Scanner-Induced Domain Shifts Undermine the Robustness of Pathology Foundation Modelscited by 9
  15. 2024Virtual birefringence imaging and histological staining of amyloid deposits in label-free tissue using autofluorescence microscopy and deep learningcited by 8
  16. 2025Foundation Models in Medical Imaging: A Review and Outlookcited by 8
  17. 2025PRISM2: Unlocking Multi-Modal General Pathology AI with Clinical Dialoguecited by 8
  18. 2024Cost-effective Instruction Learning for Pathology Vision and Language Analysiscited by 7
  19. 2024Advances in Multiple Instance Learning for Whole Slide Image Analysis: Techniques, Challenges, and Future Directionscited by 7
  20. 2024M4: Multi-Proxy Multi-Gate Mixture of Experts Network for Multiple Instance Learning in Histopathology Image Analysiscited by 6
  21. 2025Multi-Resolution Pathology-Language Pre-training Model with Text-Guided Visual Representationcited by 6
  22. 2025[De|Re]constructing VLMs' Reasoning in Countingcited by 6
  23. 2026CARE: A Molecular-Guided Foundation Model with Adaptive Region Modeling for Whole Slide Image Analysiscited by 6
  24. 2025Content Generation Models in Computational Pathology: A Comprehensive Survey on Methods, Applications, and Challengescited by 5
  25. 2025Streamline pathology foundation model by cross-magnification distillationcited by 5
  26. 2025TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilotscited by 5
  27. 2024Mamba2MIL: State Space Duality Based Multiple Instance Learning for Computational Pathologycited by 4
  28. 2024Towards a Comprehensive Benchmark for Pathological Lymph Node Metastasis in Breast Cancer Sectionscited by 4
  29. 2025Beyond Diagnostic Performance: Revealing and Quantifying Ethical Risks in Pathology Foundation Modelscited by 4
  30. 2026Mixture of Mini Experts: Overcoming the Linear Layer Bottleneck in Multiple Instance Learningcited by 4
  31. 2025MGPATH: Vision-Language Model with Multi-Granular Prompt Learning for Few-Shot WSI Classificationcited by 3
  32. 2025Can We Simplify Slide-level Fine-tuning of Pathology Foundation Models?cited by 3
  33. 2025MurreNet: Modeling Holistic Multimodal Interactions Between Histopathology and Genomic Profiles for Survival Predictioncited by 3
  34. 2026MLLM-HWSI: A Multimodal Large Language Model for Hierarchical Whole Slide Image Understandingcited by 3
  35. 2024NuLite -- Lightweight and Fast Model for Nuclei Instance Segmentation and Classificationcited by 2
  36. 2025Adaptive Prototype Learning for Multimodal Cancer Survival Analysiscited by 2
  37. 2025HiLa: Hierarchical Vision-Language Collaboration for Cancer Survival Predictioncited by 2
  38. 2025Controllable Latent Space Augmentation for Digital Pathologycited by 2

50 most cited of 108 All 108 (JSON)