Publications

A phase IIb randomised-controlled trial of the FFAR1/FFAR4 agonist icosabutate in MASH

Breast cancer HER2 scoring agreement study: pathologists vs. pathologists and AI, showing AI-measured intra-sample heterogeneity is linked to lower agreement

Interpretable predictions of toxicological liver abnormalities through multiple instance learning algorithms applied to digital whole slide images

Development and Evaluation of a Deep Learning-Based Tool for Interpretable Abnormality Detection in Preclinical Toxicology Whole Slide Images

Comprehensive characterization of granular fibrotic and cellular features in liver tissue enabled by deep learning models

AI-powered TME subtyping using human interpretable features (HIFs) from routine histopathology images in NSCLC patients treated with immunotherapy

Comparative analysis and cross-validation of Artificial Intelligence digital pathology vs. expert hepatopathologist scoring in MASLD biopsies : Results of the LITMUS Study Cohort

Analyzing patient endotypes to characterize heterogeneity in real-world data for inflammatory bowel disease

Quantitative histologic features of the inflammatory microenvironment using digital pathology prior to adalimumab treatment associate with response in patients with ulcerative colitis

Leveraging Artificial Intelligence for Enhanced Histological Scoring in Ulcerative Colitis: A Comparison with Human Pathologists​

Consortium-driven development of pathology foundation model-based approaches for automated scoring of histopathology in ulcerative colitis

CellClique: Dissecting tumor microenvironments at the single-cell level using generative AI and spatial transcriptomics

AI-powered Approaches Accurately Predict t(11;14) Positive Multiple Myeloma from H&E-stained Histologic Sections by Identifying Regions Demonstrating Lymphoplasmacytic Cytology

Artificial intelligence enables prediction of MET amplification & associated morphologic features from H&E-stained NSCLC specimens

Evaluation of an AI-powered digital pathology tool for automated tumor detection and case prioritization​

Quantitative Multimodal Anisotropy Imaging (QMAI) unveils and quantifies morphological collagen across multiple organ systems​

Machine Learning-Enabled Characterization of the Tumor Microenvironment of Post-preoperative Therapy Surgical Specimens Improves Recurrence Prediction in Patients with TNBC Treated with NAC

AI-powered detection and classification of artifacts in whole-slide images of pathology specimens

Evaluation of an AI-powered digital pathology tool for automated tumor detection and case prioritization​

AI-based triage of dermatopathology specimens for pathologist workload prioritization

Quantification of collagen and associated features from H&E-stained whole slide pathology images across cancer types using a physics-based deep learning model

Impact of a machine learning-powered algorithm on pathologist HER2 IHC scoring in breast cancer

Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2–Stained Clinical Specimens in Breast Cancer

A feasibility study using quantitative and interpretable histological analyses of celiac disease for automated cell type and tissue area classification

Multiple DP/AI Quantification approaches are complimentary in identifying histology features: cross sectional study in a Japanese cohort

Simulated machine learning-based fibrosis assessment reveals that adjusting for steatosis content in baseline and follow-up MASH biopsies can overestimate fibrosis reduction

Artificial intelligence-derived granular histological markers of inflammation and fibrosis associate with progression in patients with alcohol-related steatohepatitis

Stromal collagen features from H&E-stained whole slide images are associated with lymphocyte infiltration and survival following checkpoint inhibition in patients with non-small cell lung cancer

Machine learning-based collagen fiber quantification enables analysis of the pancreatic cancer tumor microenvironment directly from hematoxylin and eosin-stained whole slide images

Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis

Clinical validation of an AI-based pathology tool for scoring of metabolic dysfunction-associated steatohepatitis

Quantitative multimodal anisotropic imaging for fibrosis assessment in usual interstitial pneumonia

ContriMix: Scalable stain color augmentation for domain generalization without domain labels

ML-derived, quantitative histologic features of the inflammatory microenvironment after adalimumab induction treatment allow prediction of response in patients with ulcerative colitis

Assessment of PD-L1 expression and tumour infiltrating lymphocytes in early-stage non-small cell lung carcinoma with aritifical intelligence algorithms

Validation of a whole slide image management system for metabolic-associated steatohepatitis for clinical trials

Spatial mapping of immunosuppressive CAF gene signatures in H&E-stained images using additive multiple instance learning

PLUTO: Pathology-Universal Transformer

AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases

Learning biologically relevant features in a pathology foundation model using sparse autoencoders

Interpretability analysis on a pathology foundation model reveals biologically relevant embeddings across modalities

AI powered quantification of nuclear morphology in cancers enables prediction of genome instability and prognosis

Spatial Architecture of Myeloid and T Cells Orchestrates Immune Evasion and Clinical Outcome in Lung Cancer

Analytical and Clinical Validation of AIM-NASH: A Digital Pathology Tool for Artificial Intelligence-based Measurement of Nonalcoholic Steatohepatitis Histology

Classification of the Tumor Immune Microenvironment Using Machine-Learning-Based CD8 Immunophenotyping As a Potential Biomarker for Immunotherapy and TGF-β Blockade in Nonsmall Cell Lung Cancer

Scoring PD-L1 Expression in Urothelial Carcinoma: An International Multi-Institutional Study on Comparison of Manual and Artificial Intelligence Measurement Model (AIM-PD-L1) Pathology Assessments

AI-Enabled Digital Pathology: Lessons Learned From Utilization of PathAI's HER2 Algorithm

ContriMix: Unsupervised disentanglement of content and attribute for domain generalization in microscopy image analysis

Fully automated histological classification of cell types and tissue regions of celiac disease is feasible and correlates with the Marsh score

Artificial intelligence-powered assessment of pathologic response to neoadjuvant atezolizumab in patients with non-small cell lung cancer: results from LCMC3 study

Validation of Digital Pathology Platform for Metabolic-Associated Steatohepatitis for Clinical Trials

Clinical trial: Effects of pegozafermin on the liver and on metabolic comorbidities in subjects with biopsy-confirmed nonalcoholic steatohepatitis

Artificial intelligence scoring of liver biopsies in a phase II trial of semaglutide in nonalcoholic steatohepatitis

Cell-type-specific nuclear morphology predicts genomic instability and prognosis in multiple cancer types

NASH therapies head toward landmark approval

AI-based histologic scoring enables automated and reproducible assessment of enrollment criteria and endpoints in NASH clinical trials

Integration of deep learning-based histopathology and transcriptomics reveals key genes associated with fibrogenesis in patients with advanced NASH

Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology

Self-training of Machine Learning Models for Liver Histopathology: Generalization under Clinical Shifts

Additive MIL: Intrinsically Interpretable Multiple Instance Learning for Pathology

Association of artificial intelligence-powered and manual quantification of programmed death-ligand 1 (PD-L1) expression with outcomes in patients treated with nivolumab ± ipilimumab

Rethinking Machine Learning Model Evaluation in Pathology

Distinct hepatic immunological patterns are associated with the progression or inhibition of hepatocellular carcinoma

Multi stain graph fusion for multimodal integration in pathology

Improved statistical benchmarking of digital pathology models using pairwise frames evaluation

A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH Cirrhosis

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH

Digital pathology and artificial intelligence in translational medicine and clinical practice

Dissecting the Business Case for Adoption and Implementation of Digital Pathology: A White Paper from the Digital Pathology Association

PathAI ML Models Based on Human Interpretable Features Predict Clinically-Relevant Molecular Phenotypes Across Cancers

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes

Combination therapies including cilofexor and firsocostat for bridging fibrosis and cirrhosis due to NASH