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Deep Learning of Histopathological Features for the Prediction of Tumour Molecular Genetics

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Deep learning can predict survival directly from histology in clear cell renal cell carcinoma

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Social network analysis of cell networks improves deep learning for prediction of molecular pathways and key mutations in colorectal cancer

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A fusion model to predict the survival of colorectal cancer based on histopathological image and gene mutation

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Experimental Assessment of Color Deconvolution and Color Normalization for Automated Classification of Histology Images Stained with Hematoxylin and Eosin

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Interpretable tumor differentiation grade and microsatellite instability recognition in gastric cancer using deep learning

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SurvivalCNN: A deep learning-based method for gastric cancer survival prediction using radiological imaging data and clinicopathological variables

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DRD-UNet, a UNet-Like Architecture for Multi-Class Breast Cancer Semantic Segmentation

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Generative adversarial U-Net for domain-free few-shot medical diagnosis

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Multi-modality artificial intelligence in digital pathology

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Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E‐stained images: achieving state‐of‐the‐art predictive performance with fewer data using Swin Transformer

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Acute myeloid leukemia and artificial intelligence, algorithms and new scores

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Role of artificial intelligence in multidisciplinary imaging diagnosis of gastrointestinal diseases

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An integrative transcriptome analysis reveals potential predictive, prognostic biomarkers and therapeutic targets in colorectal cancer

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Application of digital pathology‐based advanced analytics of tumour microenvironment organisation to predict prognosis and therapeutic response

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Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks

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Improving feature extraction from histopathological images through a fine-tuning ImageNet model

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LifeLonger: A Benchmark for Continual Disease Classification

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Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

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Deep learning in digital pathology for personalized treatment plans of cancer patients

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Deep learning-based prediction of molecular cancer biomarkers from tissue slides: A new tool for precision oncology

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Integrative deep learning analysis improves colon adenocarcinoma patient stratification at risk for mortality

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Pseudo-Data Based Self-Supervised Federated Learning for Classification of Histopathological Images

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Role of artificial intelligence in digital pathology for gynecological cancers

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Towards fairness-aware and privacy-preserving enhanced collaborative learning for healthcare

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Predicting Metastasis Risk in Pancreatic Neuroendocrine Tumors Using Deep Learning Image Analysis

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Classification and Visualisation of Normal and Abnormal Radiographs; A Comparison between Eleven Convolutional Neural Network Architectures

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A comprehensive survey of intestine histopathological image analysis using machine vision approaches

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Unsupervised Subtyping of Cholangiocarcinoma Using a Deep Clustering Convolutional Autoencoder

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TeSLA: Test-Time Self-Learning With Automatic Adversarial Augmentation

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Deep learning predicts therapy-relevant genetics in acute myeloid leukemia from Pappenheim-stained bone marrow smears

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Requirements for implementation of artificial intelligence in the practice of gastrointestinal pathology

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Artificial intelligence for solid tumour diagnosis in digital pathology

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Machine learning in gastrointestinal surgery

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A deep learning quantified stroma-immune score to predict survival of patients with stage II–III colorectal cancer

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Machine learning approaches for classification of colorectal cancer with and without feature selection method on microarray data

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The future of artificial intelligence in digital pathology – results of a survey across stakeholder groups

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DARC: Deep adaptive regularized clustering for histopathological image classification

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Survival prediction in triple negative breast cancer using multiple instance learning of histopathological images

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Artificial Intelligence Program to Predict p53 Mutations in Ulcerative Colitis–Associated Cancer or Dysplasia

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Built to Last? Reproducibility and Reusability of Deep Learning Algorithms in Computational Pathology

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Cross-domain visual prompting with spatial proximity knowledge distillation for histological image classification

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Implementing digital pathology: qualitative and financial insights from eight leading European laboratories

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Artificial Intelligence-Powered Quality Assurance: Transforming Diagnostics, Surgery, and Patient Care—Innovations, Limitations, and Future Directions

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Advances in and the Applicability of Machine Learning-Based Screening and Early Detection Approaches for Cancer: A Primer

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Predicting neoadjuvant chemotherapy benefit using deep learning from stromal histology in breast cancer

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Automated System for Colon Cancer Detection and Segmentation Based on Deep Learning Techniques

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Deep learning detects virus presence in cancer histologyPreprint

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A Novel Artificial Intelligence–Powered Method for Prediction of Early Recurrence of Prostate Cancer After Prostatectomy and Cancer Drivers

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Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study

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FabNet: A Features Agglomeration-Based Convolutional Neural Network for Multiscale Breast Cancer Histopathology Images Classification

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Screening of normal endoscopic large bowel biopsies with interpretable graph learning: a retrospective study

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Artifact Detection and Restoration in Histology Images With Stain-Style and Structural Preservation

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Integrating AI-Powered Digital Pathology and Imaging Mass Cytometry Identifies Key Classifiers of Tumor Cells, Stroma, and Immune Cells in Non–Small Cell Lung Cancer

Rigamonti, A., Viatore, M., Polidori, R., Rahal, D., Erreni, M., Fumagalli, M. R., Zanini, D., Doni, A., Putignano, A. R., Bossi, P., et al. (2024) · Cancer Research · doi:10.1158/0008-5472.can-23-1698 · Cited by 30

Classification of colorectal tissue images from high throughput tissue microarrays by ensemble deep learning methods

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Applying artificial intelligence in the microbiome for gastrointestinal diseases: A review

Zeng, T., Yu, X., & Chen, Z. (2021) · Journal of Gastroenterology and Hepatology · doi:10.1111/jgh.15503 · Cited by 30

A self-supervised vision transformer to predict survival from histopathology in renal cell carcinoma

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Diagnosis of lymph node metastasis in head and neck squamous cell carcinoma using deep learning

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Nucleus classification in histology images using message passing network

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The role of unpaired image-to-image translation for stain color normalization in colorectal cancer histology classification

Altini, N., Marvulli, T. M., Zito, F. A., Caputo, M., Tommasi, S., Azzariti, A., Brunetti, A., Prencipe, B., Mattioli, E., Summa, S. D., et al. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107511 · Cited by 29

Deep Learning in Single-cell Analysis

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Survival prediction of stomach cancer using expression data and deep learning models with histopathological images

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Deep learning based digital pathology for predicting treatment response to first-line PD-1 blockade in advanced gastric cancer

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CPLIP: Zero-Shot Learning for Histopathology with Comprehensive Vision-Language Alignment

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Failure Detection in Deep Neural Networks for Medical Imaging

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histolab: A Python library for reproducible Digital Pathology preprocessing with automated testing

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Oral epithelial dysplasia detection and grading in oral leukoplakia using deep learning

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Lung and Colon Cancer Detection Using a Deep AI Model

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Evaluating pre-trained convolutional neural networks and foundation models as feature extractors for content-based medical image retrieval

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Automatic colon polyp classification using Convolutional Neural Network: A Case Study at Basque Country

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Machine Learning and Artificial Intelligence–driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides

Xu, H., Cong, F., & Hwang, T. H. (2021) · European Urology Focus · doi:10.1016/j.euf.2021.07.006 · Cited by 27

MTU: A multi-tasking U-net with hybrid convolutional learning and attention modules for cancer classification and gland Segmentation in Colon Histopathological Images

Dabass, M., Vashisth, S., & Vig, R. (2022) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2022.106095 · Cited by 27

Leveraging medical Twitter to build a visual–language foundation model for pathology AIPreprint

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Artificial Intelligence and the Future of Gastroenterology and Hepatology

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Exploiting Geometric Features via Hierarchical Graph Pyramid Transformer for Cancer Diagnosis Using Histopathological Images

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Continual learning in medical image analysis: A comprehensive review of recent advancements and future prospects

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Deep learning for single-lead ECG beat arrhythmia-type detection using novel iris spectrogram representation

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