> For the complete documentation index, see [llms.txt](https://www.parapathology.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.parapathology.com/clippings.md).

# Clippings

- [Clippings](https://www.parapathology.com/clippings/clippings.md)
- [Digital and Computational Pathology Applications in Bladder Cancer: Novel Tools Addressing Clinically Pressing Needs](https://www.parapathology.com/clippings/digital-and-computational-pathology-applications-in-bladder-cancer-novel-tools-addressing-clinically.md): Bladder cancer (BC) remains a major disease burden in terms of incidence, morbidity,mortality, and economic cost. Deciphering the intrinsic molecular subtypes and identificationof key drivers of BC ha
- [Immunohistochemistry in the Differential Diagnosis of... : Applied Immunohistochemistry & Molecular Morphology](https://www.parapathology.com/clippings/immunohistochemistry-in-the-differential-diagnosis-of...-applied-immunohistochemistry-and-molecular.md): Distinction of metastasis to the breast from a breast primary, particularly high-grade triple-negati
- [Introduction to Cell Profiler: A beginner’s guide to segmentation - YouTube](https://www.parapathology.com/clippings/introduction-to-cell-profiler-a-beginners-guide-to-segmentation-youtube.md): Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
- [Pancreatic ductal adenocarcinoma and its subtypes: clinical relevance of histopathology and molecular characterization, integrating the key updates of the 2026 WHO classification](https://www.parapathology.com/clippings/pancreatic-ductal-adenocarcinoma-and-its-subtypes-2026-who-classification-virchows-archiv.md): Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers, due to its late clinical presentation, early vascular, perineural, nodal and distant dissemination, and profound resist
- [MET expression by immunohistochemistry as a biomarker in pancreatic neuroendocrine tumours](https://www.parapathology.com/clippings/met-expression-by-immunohistochemistry-as-a-biomarker-in-pancreatic-neuroendocrine-tumours.md): MET (c-MET) is a receptor tyrosine kinase implicated in numerous cancers, including pancreatic neuroendocrine tumours (pNETs), by promoting cell proliferation, survival, invasion and angiogenesis. Rec
- [Emerging concepts and recent advances in renal cell neoplasia](https://www.parapathology.com/clippings/emerging-concepts-and-recent-advances-in-renal-cell-neoplasia.md): Guest editorial in Virchows Archiv by Kiril Trpkov and Abbas Agaimy highlighting emerging concepts and taxonomic evolution in renal cell neoplasia: consolidating renal hemangioblastoma (RHB) into the
- [Neuroendocrine Neoplasms of the Urinary Bladder: Integrating Molecular Advances into a Refined Classification System](https://www.parapathology.com/clippings/neuroendocrine-neoplasms-of-the-urinary-bladder-integrating-molecular-advances-into-a-refined-classi.md): Neuroendocrine neoplasms (NENs) of the urinary bladder are rare but highly aggressive tumors that account for under 1% of bladder malignancies. The 2022 WHO classification recognizes small cell neuroe
- [Pathology-CoT: learning visual chain-of-thought agents from expert whole-slide image diagnosis behaviour](https://www.parapathology.com/clippings/pathology-cot-learning-visual-chain-of-thought-agents-from-expert-whole-slide-image-diagnosis-behavi.md): Diagnosing a whole-slide image is an interactive, multistage process, yet practical agentic systems that navigate fields, adjust magnification and deliver explainable diagnoses remain lacking, largely
- [Seeds or Parasites Clinical and Histopathological](https://www.parapathology.com/clippings/seeds-or-parasites-clinical-and-histopathological.md)
- [HoVer-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images](https://www.parapathology.com/clippings/hover-net-simultaneous-segmentation-and-classification-of-nuclei-in-multi-tissue-histology-images.md): Özgün özet değil: HoVer-Net, H\&E doku görüntülerinde çekirdek örneklerini ayırmak ve türlerini belirlemek için yatay ve dikey merkez uzaklığı tahminlerini kullanan bir evrişimli sinir ağıdır.
- [Reproducibility of the Methods in Medical Imaging with Deep Learning](https://www.parapathology.com/clippings/reproducibility-of-the-methods-in-medical-imaging-with-deep-learning.md): Özgün özet değil: Simkó ve arkadaşları, 2018–2022 MIDL tam bildirilerinin kamuya açık veri ve kod depolarını inceleyerek yöntemlerin yeniden çalıştırılabilirliğine ilişkin bir kontrol listesi önerir.
- [Solving Unpopular Problems: The QuPath Story](https://www.parapathology.com/clippings/solving-unpopular-problems-the-qupath-story-the-pathologist.md): Meet the developer of the open-source digital pathology platform that's transforming image analysis across the globe. An interview with QuPath creator Peter Bankhead (University of Edinburgh) on the s
- [HERO: Histology Encoder for Robust Representation in Oncology](https://www.parapathology.com/clippings/hero-histology-encoder-for-robust-representation-in-oncology.md): HERO (Histology Encoder for Robust Representation in Oncology) is a 1.1-billion-parameter ViT-G/14 foundation model developed by Caris Life Sciences, pre-trained on a morphology-balanced corpus of 500
- [Accelerating Data Processing and Benchmarking of AI Models for Pathology](https://www.parapathology.com/clippings/accelerating-data-processing-and-benchmarking-of-ai-models-for-pathology.md)
- [DCTD Workshop on Foundation Models for Cancer: Advancing Diagnosis, Prognosis, and Treatment Response](https://www.parapathology.com/clippings/dctd-workshop-on-foundation-models-for-cancer-advancing-diagnosis-prognosis-and-treatment-response.md): A comprehensive synthesis of the NCI Division of Cancer Treatment and Diagnosis (DCTD) workshop on Foundation Models for Cancer (March 24–26, 2026). Details the transformative applications of self-sup
- [Distance-based evaluation of tumor budding in colorectal cancer](https://www.parapathology.com/clippings/distance-based-evaluation-of-tumor-budding-in-colorectal-cancer.md): Evaluation of tumor budding distance (average distance from tumor bulk to the three farthest buds, cutoff ≥123 µm) across 1,876 CRC patients in two independent cohorts — correlates with aggressive fea
- [From whole-slide image to biomarker prediction: end-to-end weakly supervised deep learning in computational pathology](https://www.parapathology.com/clippings/from-whole-slide-image-to-biomarker-prediction-end-to-end-weakly-supervised-deep-learning-in-computa.md)
- [NCBI Linked Discoveries: Literature Exploration and Research Neighborhood Mapping](https://www.parapathology.com/clippings/ncbi-linked-discoveries-literature-exploration-and-research-neighborhood-mapping.md): A comprehensive synthesis and guide to NCBI Linked Discoveries (v1.0, September 2026), an experimental NLM/NIH biomedical literature exploration platform. Details the BiomedBERT semantic embedding eng
- [Recommendations for reporting tumor budding in colorectal cancer based on the International Tumor Budding Consensus Conference (ITBCC) 2016](https://www.parapathology.com/clippings/recommendations-for-reporting-tumor-budding-in-colorectal-cancer-based-on-the-international-tumor-bu.md): Consensus recommendations from the International Tumor Budding Consensus Conference (ITBCC) 2016 establishing standardized criteria, a 0.785 mm² hotspot area, H\&E assessment, and a 3-tier scoring syst
- [Towards robust foundation models for digital pathology](https://www.parapathology.com/clippings/towards-robust-foundation-models-for-digital-pathology.md): Biomedical Foundation Models (FMs) are transforming AI-enabled healthcare research and entering clinical validation. However, their susceptibility to learning non-biological features — including varia
- [A distributional robustness margin for pathology foundation models](https://www.parapathology.com/clippings/a-distributional-robustness-margin-for-pathology-foundation-models.md): Pathology foundation models encode non-biological variation introduced by tissue preparation, staining and scanning, enabling shortcut learning that undermines generalisation across institutions. The
- [Awesome Fly: Curated Fruit Fly Connectome Projects](https://www.parapathology.com/clippings/awesome-fly-curated-fruit-fly-connectome-projects.md): A curated collection of fruit fly (Drosophila melanogaster) connectome projects, covering MaleCNS, FlyWire, brain simulations, embodied models, games, and research tools by Mert Cobanov.
- [Statistical Rethinking (2026 Edition)](https://www.parapathology.com/clippings/statistical-rethinking-2026-edition.md): Statistical Rethinking (2026 Edition) by Richard McElreath (MPI-EVA). A practical course on Bayesian data analysis, causal inference with DAGs, generative modeling, multilevel models, and computationa
- [When Two Wrongs Don't Make a Right: Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology](https://www.parapathology.com/clippings/when-two-wrongs-dont-make-a-right-examining-confirmation-bias-and-the-role-of-time-pressure-during-h.md): Twenty-eight pathologists estimated tumour cell percentage (TCP) twice across 20 H\&E patches, two weeks apart, the second time with an AI model under time pressure manipulations. When the AI predictio
- [Cognitive biases in AI-assisted medical decision making: A structured review as a primer for veterinary and human pathology](https://www.parapathology.com/clippings/cognitive-biases-in-ai-assisted-medical-decision-making-a-structured-review-as-a-primer-for-veterina.md): A structured literature review across ACM, IEEE, and PubMed evaluating cognitive biases in AI-assisted medical decision making. Across all medical fields, only 8 primary studies empirically measured c
- [From Samples to Knowledge 2025: QuPath Training Course](https://www.parapathology.com/clippings/from-samples-to-knowledge-2025-qupath-training-course.md): From Samples to Knowledge 2025 (FS2K) QuPath Training Course by Zbigniew Mikulski and Sara McArdle (La Jolla Institute for Immunology). A comprehensive hands-on workshop covering multiplex immunofluor
- [Navigating foundation model selection in digital pathology through performance evaluation and tradeoff analysis](https://www.parapathology.com/clippings/navigating-foundation-model-selection-in-digital-pathology-through-performance-evaluation-and-tradeo.md): Benchmarking six digital pathology foundation models (Lunit, Kaiko-Base, Phikon-v2, UNI2, Virchow2, and Kaiko-Midnight; 22M to 1.1B parameters) across WSI-level classification, WSI-level survival pred
- [The Gold Standard Paradox in Digital Image Analysis: Manual Versus Automated Scoring as Ground Truth](https://www.parapathology.com/clippings/the-gold-standard-paradox-in-digital-image-analysis-manual-versus-automated-scoring-as-ground-truth.md): Context: Novel therapeutics often target complex cellular mechanisms. Increasingly, quantitative methods like digital tissue image analysis (tIA) are required to evaluate correspondingly complex bioma
- [Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis](https://www.parapathology.com/clippings/clinical-validation-of-an-ai-based-pathology-tool-for-scoring-of-metabolic-dysfunction-associated-st.md): Metabolic dysfunction-associated steatohepatitis (MASH) is a major cause of liver-related morbidity and mortality, yet treatment options are limited. Manual scoring of liver biopsies, currently the go
- [Ethical guidelines for deploying artificial intelligence applications in the pathology field: Lessons learned from a prospective framework in a large tertiary care academic medical center](https://www.parapathology.com/clippings/ethical-guidelines-for-deploying-artificial-intelligence-applications-in-the-pathology-field-lessons.md): Several artificial intelligence (AI) algorithms have been developed with inherent age, sex, gender, racial, and ethnic biases. In pathology, this leads to marked performance disparities across differe
- [Screening efficiency over experience: Rapid target detection in low-power field as a modifiable cognitive biomarker for diagnostic accuracy in digital cytology](https://www.parapathology.com/clippings/screening-efficiency-over-experience-rapid-target-detection-in-low-power-field-as-a-modifiable-cogni.md): Eye-tracking study of 100 cytotechnologists (1–40 years experience) and 28 students evaluating 30 digital cytology images. Demonstrates the 'experience paradox': professional experience showed no sign
- [A Hybrid MIL Approach Leveraging Convolution and State-Space Model for Whole-Slide Image Cancer Subtyping](https://www.parapathology.com/clippings/a-hybrid-mil-approach-leveraging-convolution-and-state-space-model-for-whole-slide-image-cancer-subt.md): ConvMixerSSM integrates depthwise separable convolutions (ConvMixer) for localized tissue texture modeling with linear state-space models (SSM/Mamba) for global contextual reasoning and a ReLU-gated a
- [Development and initial validation of a deep learning algorithm to quantify histological features in colorectal carcinoma including tumour budding/poorly differentiated clusters](https://www.parapathology.com/clippings/development-and-initial-validation-of-a-deep-learning-algorithm-to-quantify-histological-features-in.md): To develop and validate a deep learning algorithm to quantify a broad spectrum of histological features in colorectal carcinoma. A deep learning algorithm was trained on haematoxylin and eosin-stained
- [Multiplex Immunofluorescence Image Analysis with QuPath — Part 1: Understanding Digital Images](https://www.parapathology.com/clippings/multiplex-immunofluorescence-image-analysis-with-qupath-part-1.md): This repository contains the training materials for Part 1 of the Multiplex Immunofluorescence Image Analysis with QuPath workshop. This introductory section provides the foundational knowledge requir
- [CytoFormer: A Molecularly Supervised Cell Foundation Model for Histopathology Cell Classification](https://www.parapathology.com/clippings/cytoformer-a-molecularly-supervised-cell-foundation-model-for-histopathology-cell-classification.md): CytoFormer replaces manual pathologist cell annotation with molecular supervision from paired in situ spatial transcriptomics (81 Xenium sections, 15.4M cells, 16 organs, 23 cell types). Built on a Vi
- [HistoPLUS: Towards Comprehensive Cellular Characterisation of H\&E Slides](https://www.parapathology.com/clippings/histoplus-towards-comprehensive-cellular-characterisation-of-h-and-e-slides.md): HistoPLUS combines an active-learning pan-cancer dataset (HistoTRAIN: 108k nuclei, 13 cell types, 6 indications) with a compact CellViT architecture powered by a distilled pathology foundation model (
- [CellPrior-Net: Prior-Guided Nuclei Detection and Classification for H\&E Whole-Slide Images](https://www.parapathology.com/clippings/cellprior-net-prior-guided-nuclei-detection-and-classification-for-h-and-e-whole-slide-images.md): CellPrior-Net (CP-Net) introduces an efficient, prior-guided CNN architecture for dense nuclei detection and 3-class classification (tumor, immune, other) on H\&E gigapixel whole-slide images. By coupl
- [Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs](https://www.parapathology.com/clippings/scaling-up-your-kernels-to-31x31-revisiting-large-kernel-design-in-cnns.md): Landmark CVPR 2022 paper introducing RepLKNet, which challenges the decade-long convention of small 3x3 kernels by demonstrating that large depthwise convolutions (up to 31x31) coupled with structural
- [Class visualizations and activation atlases for computational pathology](https://www.parapathology.com/clippings/class-visualizations-and-activation-atlases-for-computational-pathology.md): The clinical promise of computational pathology increasingly depends on foundation model-based pipelines, yet the morphological concepts encoded by these systems remain poorly understood. We address t
- [Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology](https://www.parapathology.com/clippings/artificial-intelligence-enables-quantitative-assessment-of-ulcerative-colitis-histology.md): Ulcerative colitis is a chronic inflammatory bowel disease that is characterized by a relapsing and remitting course. Assessment of disease activity critically informs treatment decisions. In addition
- [Considerations for digital pathology displays](https://www.parapathology.com/clippings/considerations-for-digital-pathology-displays.md): A review of digital pathology displays and guidance from the National Pathology Imaging Co-operative (NPIC) and Leeds/Linköping teams. Proposes procurement specifications informed by the commercial pr
- [NPIC Quality Coordination Centre: Digital Pathology Quality Assurance and Metrology](https://www.parapathology.com/clippings/npic-quality-coordination-centre-digital-pathology-quality-assurance-and-metrology.md): A comprehensive synthesis of the National Pathology Imaging Co-operative (NPIC) Quality Coordination Centre (QCC) based at Leeds Teaching Hospitals NHS Trust. Documents the full-lifecycle digital path
- [The pathology report as a boundary object: From clinical communication to computational representation](https://www.parapathology.com/clippings/the-pathology-report-as-a-boundary-object-from-clinical-communication-to-computational-representatio.md): A theoretical framework by Shuoshuo Wang (Harvard Medical School / Broad Institute) in Precision Pathology examining the pathology report as a semantically compressed boundary object (Star & Griesemer
- [Pangram: AI Content Detection Platform and Pangram 4 Classifier](https://www.parapathology.com/clippings/pangram-ai-content-detection-platform-and-pangram-4-classifier.md): A comprehensive synthesis of Pangram (Pangram Labs), the enterprise AI content and text detection platform, its foundational classifier architecture, and the Pangram 4 Technical Report (arXiv:2607.271
- [Study on the Performance of Different Cover Glasses in Microscopy](https://www.parapathology.com/clippings/study-on-the-performance-of-different-cover-glasses-in-microscopy.md): A comprehensive optical metrology and ray-tracing evaluation comparing conventional glass coverslips (Leica HistoCore SPECTRA CV) with polymer film tape (Sakura Tissue-Tek). Documents tactile profilom
- [Robotic microscopy for everyone: the OpenFlexure Microscope](https://www.parapathology.com/clippings/robotic-microscopy-for-everyone-the-openflexure-microscope.md): A comprehensive synthesis of the OpenFlexure Microscope platform and foundational research papers in Biomedical Optics Express (Collins et al., 2020) and Review of Scientific Instruments (Sharkey et a
- [A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification](https://www.parapathology.com/clippings/a-feasibility-study-using-quantitative-and-interpretable-histological-analyses-of-celiac-disease-for.md): Histological assessment is essential for the diagnosis and management of celiac disease. Current scoring systems, including modified Marsh (Marsh-Oberhuber) score, lack inter-pathologist agreement. To
- [HistoGen: Histopathology Cell Nuclei Image Generation Tool](https://www.parapathology.com/clippings/histogen-histopathology-cell-nuclei-image-generation-tool.md): An open-source computational pathology toolbox and conditional diffusion model (DDPM) developed by the FDA Center for Devices and Radiological Health (CDRH/DIDSR, Regulatory Science Tool RST26DP02.01)
- [Regulatory Science Tools Catalog: Digital Pathology (FDA CDRH)](https://www.parapathology.com/clippings/regulatory-science-tools-catalog-digital-pathology.md): A comprehensive synthesis of the FDA Center for Devices and Radiological Health (CDRH) Catalog of Regulatory Science Tools (RST) for Digital Pathology (Program Area 26). Details all five peer-reviewed
- [From Model to Patient: M-Optimus-1 for Spatial Biomarker Discovery in Ovarian Cancer](https://www.parapathology.com/clippings/from-model-to-patient-m-optimus-1-for-spatial-biomarker-discovery-in-ovarian-cancer.md): Bioptimus demonstrates the application of M-Optimus-1, a multimodal biological foundation world model, for in silico spatial transcriptomics (6,000 genes) directly from H\&E whole-slide images and bulk
- [Performance of an Artificial Intelligence Model for Recognition and Quantitation of Histologic Features of Eosinophilic Esophagitis on Biopsy Samples](https://www.parapathology.com/clippings/performance-of-an-artificial-intelligence-model-for-recognition-and-quantitation-of-histologic-featu.md): We have developed an artificial intelligence (AI)-based digital pathology model for the evaluation of histologic features related to eosinophilic esophagitis (EoE). In this study, we evaluated the per
- [Standardization in digital pathology: Supplement 145 of the DICOM standards](https://www.parapathology.com/clippings/standardization-in-digital-pathology-supplement-145-of-the-dicom-standards.md): Foundational review detailing DICOM Standards Committee Working Group 26 (WG-26) Supplement 145, which established the vendor-neutral Whole Slide Microscopic Image Information Object Definition (IOD)
- [Towards deep-learning based detection and quantification of intestinal metaplasia on digitized gastric biopsies: a multi-expert comparative study](https://www.parapathology.com/clippings/towards-deep-learning-based-detection-and-quantification-of-intestinal-metaplasia-on-digitized-gastr.md): Current gastric cancer (GCa) risk systems are prone to errors since they evaluate a visual estimation of intestinal metaplasia percentages in histopathology images of gastric mucosa to assign a risk.
- [LFABP: Liver Fatty Acid Binding Protein](https://www.parapathology.com/clippings/lfabp-liver-fatty-acid-binding-protein.md): Comprehensive diagnostic pathology digest on Liver Fatty Acid Binding Protein (LFABP / FABP1) immunohistochemistry. Covers physiological expression under HNF1A transcriptional control, diagnostic util
- [ETV4: ETS Variant Transcription Factor 4](https://www.parapathology.com/clippings/etv4-ets-variant-transcription-factor-4.md): Comprehensive diagnostic pathology digest on ETV4 (ETS Variant Transcription Factor 4 / PEA3 / E1AF) immunohistochemistry. Focuses on its role as a surrogate nuclear marker for CIC-rearranged round ce
- [PROX1: Prospero Homeobox 1](https://www.parapathology.com/clippings/prox1-prospero-homeobox-1.md): Comprehensive diagnostic pathology digest on PROX1 (Prospero Homeobox 1) immunohistochemistry. Focuses on its role as the master nuclear transcription factor governing lymphatic endothelial differenti
- [Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning](https://www.parapathology.com/clippings/improving-the-accuracy-of-gastrointestinal-neuroendocrine-tumor-grading-with-deep-learning.md): The Ki-67 index is an established prognostic factor in gastrointestinal neuroendocrine tumors (GI-NETs) and defines tumor grade. It is currently estimated by microscopically examining tumor tissue sin
- [A Deep Learning Model of Histologic Tumor Differentiation as a Prognostic Tool in Hepatocellular Carcinoma](https://www.parapathology.com/clippings/a-deep-learning-model-of-histologic-tumor-differentiation-as-a-prognostic-tool-in-hepatocellular-car.md): Tumor differentiation represents an important driver of the biological behavior of various forms of cancer. Histologic features of tumor differentiation in hepatocellular carcinoma (HCC) include cytoa
- [A deep-learning-based model for assessment of autoimmune hepatitis from histology: AI(H)](https://www.parapathology.com/clippings/a-deep-learning-based-model-for-assessment-of-autoimmune-hepatitis-from-histology-ai-h.md): Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results of these challenges, nonclassical features such as bile-duct injury stays understudied in AIH. We a
- [Stroma and lymphocytes identified by deep learning are independent predictors for survival in pancreatic cancer](https://www.parapathology.com/clippings/stroma-and-lymphocytes-identified-by-deep-learning-are-independent-predictors-for-survival-in-pancre.md): Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancers known to humans. However, not all patients fare equally poor survival, and a minority of patients even survives advanced disea
- [Beyond root cause analysis: a practical systems engineering approach to incident investigation in histopathology](https://www.parapathology.com/clippings/beyond-root-cause-analysis-a-practical-systems-engineering-approach-to-incident-investigation-in-his.md): Patient safety and diagnostic quality are central to modern histopathology, yet incident investigation remains heavily reliant on root cause analysis (RCA). While RCA offers an established mechanism f
- [Ambient, real-time digitization and datafication of glass slide microscopy towards AI-at-the-microscope](https://www.parapathology.com/clippings/ambient-real-time-digitization-and-datafication-of-glass-slide-microscopy-towards-ai-at-the-microsco.md): Pathology remains central to clinical diagnosis, yet adoption of digital pathology is constrained by financial, operational, and workflow burdens of fully digital infrastructure. We introduce HistoCAM
- [From operating room to pathology report: Delphi consensus on pathological assessment of peritoneal cytology and biopsies in staging laparoscopy for gastric cancer](https://www.parapathology.com/clippings/from-operating-room-to-pathology-report-delphi-consensus-on-pathological-assessment-of-peritoneal-cy.md): Background: Staging laparoscopy with peritoneal cytology and biopsies is recommended in selected patients with gastric cancer (GC), but practical guidance for assessment of peritoneal lavage/ascites a
- [Guidance for laboratory implementation, governance and continuous assurance of artificial intelligence in histopathology](https://www.parapathology.com/clippings/guidance-for-laboratory-implementation-governance-and-continuous-assurance-of-artificial-intelligenc.md): Artificial intelligence (AI) is rapidly transforming histopathology, with applications ranging from workflow optimisation and quality assurance to tumour diagnosis, grading, biomarker assessment and e