> 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/appendix.md).

# Appendix

- [Appendix](https://www.parapathology.com/appendix/appendix.md)
- [Courses and MOOCs](https://www.parapathology.com/appendix/courses-and-moocs.md)
- [Computer Programs and Applications](https://www.parapathology.com/appendix/computer-programs-and-applications.md)
- [Books](https://www.parapathology.com/appendix/books.md)
- [Web Pages](https://www.parapathology.com/appendix/web-pages.md): Appendix : Suggested Web Pages
- [Videos](https://www.parapathology.com/appendix/videos.md)
- [GitHub Repositories](https://www.parapathology.com/appendix/github-repositories.md)
- [Yazmayıp da beslese miydik](https://www.parapathology.com/appendix/yazmayip-da-beslese-miydik.md)
- [Deutsche Artikel](https://www.parapathology.com/appendix/deutsche-artikel.md)
- [Clippings](https://www.parapathology.com/appendix/clippings.md)
- [Digital and Computational Pathology Applications in Bladder Cancer: Novel Tools Addressing Clinically Pressing Needs](https://www.parapathology.com/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/clippings/seeds-or-parasites-clinical-and-histopathological.md)
- [Solving Unpopular Problems: The QuPath Story](https://www.parapathology.com/appendix/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
- [Distance-based evaluation of tumor budding in colorectal cancer](https://www.parapathology.com/appendix/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
- [Recommendations for reporting tumor budding in colorectal cancer based on the International Tumor Budding Consensus Conference (ITBCC) 2016](https://www.parapathology.com/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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/appendix/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 (
- [Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology](https://www.parapathology.com/appendix/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/appendix/clippings/considerations-for-digital-pathology-displays.md): A comprehensive examination of the digital pathology display landscape from the National Pathology Imaging Co-operative (NPIC) and Leeds/Linköping teams. Reviews 56 international professional and regu
- [A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification](https://www.parapathology.com/appendix/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/appendix/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/appendix/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
- [Performance of an Artificial Intelligence Model for Recognition and Quantitation of Histologic Features of Eosinophilic Esophagitis on Biopsy Samples](https://www.parapathology.com/appendix/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
- [Towards deep-learning based detection and quantification of intestinal metaplasia on digitized gastric biopsies: a multi-expert comparative study](https://www.parapathology.com/appendix/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.
- [Improving the accuracy of gastrointestinal neuroendocrine tumor grading with deep learning](https://www.parapathology.com/appendix/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/appendix/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/appendix/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/appendix/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
- [miscellaneous](https://www.parapathology.com/appendix/miscellaneous.md): Miscellaneous links to be organised. Ordan burdan derlenmiş ama düzenlenmemiş güncel patoloji içerikleri. https://www.parapathology.com/appendix/miscellaneous