On the public citation graph
High-Throughput, Machine Learning–Based Quantification of Steatosis, Inflammation, Ballooning, and Fibrosis in Biopsies From Patients With Nonalcoholic Fatty Liver Disease
0 signed · 172 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/hep.20701openalex-snapshot
Design and validation of a histological scoring system for nonalcoholic fatty liver disease†
inferredcites →https://doi.org/10.1002/hep.22724openalex-snapshot
Portal chronic inflammation in nonalcoholic fatty liver disease (NAFLD)
inferredcites →https://doi.org/10.1002/hep.22745openalex-snapshot
Computer-assisted image analysis of liver collagen: Relationship to Ishak scoring and hepatic venous pressure gradient #
inferredcites →https://doi.org/10.1002/hep.24127openalex-snapshot
Nonalcoholic Fatty Liver Disease (NAFLD) Activity Score and the Histopathologic Diagnosis in NAFLD: Distinct Clinicopathologic Meanings §Δ
inferredcites →https://doi.org/10.1002/hep.27173openalex-snapshot
Utility and appropriateness of the fatty liver inhibition of progression (FLIP) algorithm and steatosis, activity, and fibrosis (SAF) score in the evaluation of biopsies of nonalcoholic fatty liver disease
inferredcites →https://doi.org/10.1002/hep.27368openalex-snapshot
Fibrosis stage is the strongest predictor for disease‐specific mortality in NAFLD after up to 33 years of follow‐up
inferredcites →https://doi.org/10.1002/hep.28374openalex-snapshot
Portal inflammation is independently associated with fibrosis and metabolic syndrome in pediatric nonalcoholic fatty liver disease
inferredcites →https://doi.org/10.1002/hep.29607openalex-snapshot
Case definitions for inclusion and analysis of endpoints in clinical trials for nonalcoholic steatohepatitis through the lens of regulatory science
inferredcites →https://doi.org/10.1016/j.cld.2015.10.001openalex-snapshot
Epidemiology of Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis in the United States and the Rest of the World
inferredcites →https://doi.org/10.1016/j.cmpb.2016.11.012openalex-snapshot
A methodology for automated CPA extraction using liver biopsy image analysis and machine learning techniques
inferredcites →https://doi.org/10.1016/j.humpath.2010.07.013openalex-snapshot
Comparing morphometric, biochemical, and visual measurements of macrovesicular steatosis of liver
inferredcites →https://doi.org/10.1016/j.humpath.2015.01.019openalex-snapshot
Automatic quantification of lobular inflammation and hepatocyte ballooning in nonalcoholic fatty liver disease liver biopsies
inferredcites →https://doi.org/10.1016/j.jhep.2015.11.004openalex-snapshot
EASL–EASD–EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease
inferredcites →https://doi.org/10.1016/j.jhep.2017.07.027openalex-snapshot
Fibrosis stage but not NASH predicts mortality and time to development of severe liver disease in biopsy-proven NAFLD
inferredcites →https://doi.org/10.1016/s0016-5085(19)35563-5openalex-snapshot
One-Second Needle Biopsy of the Liver
inferredcites →https://doi.org/10.1016/s0168-8278(00)80397-9openalex-snapshot
Automatic quantification of liver fibrosis: design and validation of a new image analysis method: comparison with semi-quantitative indexes of fibrosis
inferredcites →https://doi.org/10.1016/s0168-8278(18)30458-6openalex-snapshot
A deep-learning approach for pattern recognition allows rapid and reproducible quantification of histological NASH parameters: Integration into the QuPath platform
inferredcites →https://doi.org/10.1016/s2468-1253(17)30184-xopenalex-snapshot
Surrogate endpoints for clinical trials in non-alcoholic steatohepatitis
inferredcites →https://doi.org/10.1034/j.1600-0676.2003.01771.xopenalex-snapshot
Quantitative versus morphological assessment of liver fibrosis: semi‐quantitative scores are more robust than digital image fibrosis area estimation
inferredcites →https://doi.org/10.1053/j.gastro.2014.11.039openalex-snapshot
Nonalcoholic Steatohepatitis Is the Second Leading Etiology of Liver Disease Among Adults Awaiting Liver Transplantation in the United States
inferredcites →https://doi.org/10.1053/j.gastro.2015.04.043openalex-snapshot
Liver Fibrosis, but No Other Histologic Features, Is Associated With Long-term Outcomes of Patients With Nonalcoholic Fatty Liver Disease
inferredcites →https://doi.org/10.1097/mcg.0b013e3181dd1348openalex-snapshot
Generalizability of the Nonalcoholic Steatohepatitis Clinical Research Network Histologic Scoring System for Nonalcoholic Fatty Liver Disease
inferredcites →https://doi.org/10.1097/sla.0b013e3181bcd6ddopenalex-snapshot
Assessment of Hepatic Steatosis by Expert Pathologists
inferredcites →https://doi.org/10.1111/apt.13051openalex-snapshot
Quantification of fibrosis by collagen proportionate area predicts hepatic decompensation in hepatitis C cirrhosis
inferredcites →https://doi.org/10.1111/apt.15219openalex-snapshot
Collagen proportionate area is an independent predictor of long‐term outcome in patients with non‐alcoholic fatty liver disease
inferredcites →https://doi.org/10.1111/j.1572-0241.1999.01377.xopenalex-snapshot
Nonalcoholic Steatohepatitis: A Proposal for Grading and Staging The Histological Lesions
inferredcites →https://doi.org/10.1111/liv.12162openalex-snapshot
Hepatic steatosis estimated microscopically versus digital image analysis
inferredcites →https://doi.org/10.1177/001316447303300309openalex-snapshot
The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability
inferredcites →https://doi.org/10.1309/w3xc-nt4h-kfbn-2g0bopenalex-snapshot
A Systematic Review of the Quality of Liver Biopsy Specimens
inferredcites →https://doi.org/10.1371/journal.pone.0199166openalex-snapshot
Second harmonic generation microscopy provides accurate automated staging of liver fibrosis in patients with non-alcoholic fatty liver disease
inferredcites →https://doi.org/10.14670/hh-24.49openalex-snapshot
An innovative methodology for the automated morphometric and quantitative estimation of liver steatosis.
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4481966openalex-extracted
Artificial Intelligence in Identifying Patients with Undiagnosed Nonalcoholic Steatohepatitis
inferred← citeshttps://doi.org/10.1002/dmrr.70129openalex-snapshot
Recent Advances in the Application of Machine Learning Models in Metabolic Dysfunction–Associated Steatotic Liver Disease
inferred← citeshttps://doi.org/10.1002/hep.31603openalex-snapshot
Application of Artificial Intelligence for the Diagnosis and Treatment of Liver Diseases
inferred← citeshttps://doi.org/10.1002/hep.31750openalex-snapshot
A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH
inferred← citeshttps://doi.org/10.1002/hep.31869openalex-snapshot
Application of Artificial Intelligence for Diagnosis and Risk Stratification in NAFLD and NASH: The State of the Art
inferred← citeshttps://doi.org/10.1002/hep.32087openalex-snapshot
A Machine Learning Approach to Liver Histological Evaluation Predicts Clinically Significant Portal Hypertension in NASH Cirrhosis
inferred← citeshttps://doi.org/10.1002/hep.32329openalex-snapshot
The digital transformation of hepatology: The patient is logged in
inferred← citeshttps://doi.org/10.1002/ima.22936openalex-snapshot
Grading of steatosis, fibrosis, lobular inflammation, and ballooning from liver pathology images using pre‐trained convolutional neural networks
inferred← citeshttps://doi.org/10.1002/ima.23123openalex-snapshot
A Deep Learning Method Enables Quantitative and Automatic Measurement of Rat Liver Histology in NAFLD
inferred← citeshttps://doi.org/10.1002/ird3.24openalex-snapshot
Radiobioinformatics: A novel bridge between basic research and clinical practice for clinical decision support in diffuse liver diseases
inferred← citeshttps://doi.org/10.1002/jgh3.12716openalex-snapshot
Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis
inferred← citeshttps://doi.org/10.1002/jmv.29863openalex-snapshot
A novel model based on serum N‐glycan markers for evaluating stage of liver necroinflammation in treatment‐naïve chronic hepatitis B patients
inferred← citeshttps://doi.org/10.1002/jpn3.70166openalex-snapshot
A prediction model for genetic cholestatic disease in infancy using the machine learning approach
inferred← citeshttps://doi.org/10.1007/978-3-030-87240-3_15openalex-snapshot
Focusing on Clinically Interpretable Features: Selective Attention Regularization for Liver Biopsy Image Classification
inferred← citeshttps://doi.org/10.1007/978-3-031-58604-0_11openalex-snapshot
AI-Powered Automated Methods for Predicting Liver Disease: A Recent Review
inferred← citeshttps://doi.org/10.1007/978-3-031-94950-0_31openalex-snapshot
Deep Learning Predicts Non-human Primate Drinking Category from Liver Histology
inferred← citeshttps://doi.org/10.1007/978-981-97-5345-1_2openalex-snapshot
From Pixels to Predictions: Exploring the Role of Artificial Intelligence in Radiology
inferred← citeshttps://doi.org/10.1007/s00261-024-04622-zopenalex-snapshot
Radiologic correlation with fatty liver and adrenal adenoma using dual echo chemical shift magnetic resonance imaging
inferred← citeshttps://doi.org/10.1007/s00292-024-01298-6openalex-snapshot
Herausforderungen der Automation bei der quantitativen Auswertung von Leberbiopsien
inferred← citeshttps://doi.org/10.1007/s00330-023-09735-5openalex-snapshot
Correlation of histologic, imaging, and artificial intelligence features in NAFLD patients, derived from Gd-EOB-DTPA-enhanced MRI: a proof-of-concept study
inferred← citeshttps://doi.org/10.1007/s00428-023-03496-8openalex-snapshot
Zonated quantification of immunohistochemistry in normal and steatotic livers
inferred← citeshttps://doi.org/10.1007/s11095-024-03791-2openalex-snapshot
A Model-Based Evaluation of Noninvasive Biomarkers to Reflect Histological Nonalcoholic Fatty Liver Disease Scores
inferred← citeshttps://doi.org/10.1007/s11154-021-09681-xopenalex-snapshot
Applications of artificial intelligence (AI) in researches on non-alcoholic fatty liver disease(NAFLD) : A systematic review
inferred← citeshttps://doi.org/10.1007/s13246-025-01659-2openalex-snapshot
Attention-based graph neural network framework for non-invasive CAP score prediction in fatty liver disease via body modeling
inferred← citeshttps://doi.org/10.1016/b978-0-12-820239-5.00002-4openalex-snapshot
History, current status, and future directions of artificial intelligence
inferred← citeshttps://doi.org/10.1016/b978-0-323-99136-0.00003-9openalex-snapshot
Artificial intelligence in prediction of steatosis and fibrosis of nonalcoholic fatty liver disease
inferred← citeshttps://doi.org/10.1016/b978-0-443-15688-5.00016-4openalex-snapshot
Artificial intelligence in gastroenterology and hepatology
inferred← citeshttps://doi.org/10.1016/b978-0-443-15728-8.00002-1openalex-snapshot
Digital health in hepatology
inferred← citeshttps://doi.org/10.1016/b978-0-443-15842-1.00013-2openalex-snapshot
High content screening in toxicology
inferred← citeshttps://doi.org/10.1016/b978-0-443-40383-5.00008-xopenalex-snapshot
Applications of artificial intelligence in surgical pathology
inferred← citeshttps://doi.org/10.1016/b978-0-7020-8228-3.00005-3openalex-snapshot
Fatty Liver Disease
inferred← citeshttps://doi.org/10.1016/bs.vh.2022.09.006openalex-snapshot
Free radicals, antioxidants, nuclear factor-E2-related factor-2 and liver damage
inferred← citeshttps://doi.org/10.1016/j.addr.2021.04.018openalex-snapshot
Translating complexity and heterogeneity of pancreatic tumor: 3D in vitro to in vivo models
inferred← citeshttps://doi.org/10.1016/j.ajpath.2023.04.014openalex-snapshot
Deep Learning–Based Image Analysis of Liver Steatosis in Mouse Models
inferred← citeshttps://doi.org/10.1016/j.aohep.2024.101528openalex-snapshot
Accurate prediction of all-cause mortality in patients with metabolic dysfunction-associated steatotic liver disease using electronic health records
inferred← citeshttps://doi.org/10.1016/j.autrev.2021.103014openalex-snapshot
Assessing and counteracting fibrosis is a cornerstone of the treatment of CKD secondary to systemic and renal limited autoimmune disorders
inferred← citeshttps://doi.org/10.1016/j.cgh.2022.05.027openalex-snapshot
Artificial Intelligence Improves Pathologist Agreement for Fibrosis Scores in Nonalcoholic Steatohepatitis Patients
inferred← citeshttps://doi.org/10.1016/j.cgh.2023.04.007openalex-snapshot
Artificial Intelligence Applications in Hepatology
inferred← citeshttps://doi.org/10.1016/j.cgh.2025.09.011openalex-snapshot
Morphometric Quantification of Steatosis and Fibrosis in Metabolic Liver Disease Associated With Type 2 Diabetes
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2025.110049openalex-snapshot
Liver-Quant: Feature-based image analysis toolkit for automatic quantification of metabolic dysfunction-associated steatotic liver disease
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2026.111619openalex-snapshot
Artificial intelligence for metabolic dysfunction-associated steatotic liver disease diagnosis: A systematic review
inferred← citeshttps://doi.org/10.1016/j.csbj.2023.03.048openalex-snapshot
Artificial intelligence and deep learning: New tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis
inferred← citeshttps://doi.org/10.1016/j.csbj.2024.07.008openalex-snapshot
Hepatic encephalopathy post-TIPS: Current status and prospects in predictive assessment
inferred← citeshttps://doi.org/10.1016/j.ebiom.2024.105127openalex-snapshot
Multi-tissue profiling of oxylipins reveal a conserved up-regulation of epoxide:diol ratio that associates with white adipose tissue inflammation and liver steatosis in obesity
inferred← citeshttps://doi.org/10.1016/j.eclinm.2023.102419openalex-snapshot
Development of a machine learning-based model to predict hepatic inflammation in chronic hepatitis B patients with concurrent hepatic steatosis: a cohort study
inferred← citeshttps://doi.org/10.1016/j.engappai.2024.109452openalex-snapshot
Artificial intelligence-powered precision: Unveiling the landscape of liver disease diagnosis—A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.heliyon.2024.e38848openalex-snapshot
A machine learning-based predictive model discriminates nonalcoholic steatohepatitis from nonalcoholic fatty liver disease
inferred← citeshttps://doi.org/10.1016/j.ibmed.2026.100386openalex-snapshot
Artificial intelligence and the evolution of pathology: Scaling from digital diagnostics to multimodal precision medicine
inferred← citeshttps://doi.org/10.1016/j.iliver.2026.100225openalex-snapshot
Development of a hybrid deep learning-based framework for liver fibrosis classification using ultrasound images
inferred← citeshttps://doi.org/10.1016/j.jare.2025.08.042openalex-snapshot
Application of machine learning and deep learning in metabolic dysfunction-associated steatotic liver disease: a systematic review and meta-analysis
inferred← citeshttps://doi.org/10.1016/j.jceh.2022.12.003openalex-snapshot
Automated Segmentation and Morphological Characterization of Hepatic Steatosis and Correlation with Histopathology
inferred← citeshttps://doi.org/10.1016/j.jhep.2020.06.025openalex-snapshot
Suboptimal reliability of liver biopsy evaluation has implications for randomized clinical trials
inferred← citeshttps://doi.org/10.1016/j.jhep.2020.08.025openalex-snapshot
NAFLD: Time to apply quantitation in liver biopsies as endpoints in clinical trials
inferred← citeshttps://doi.org/10.1016/j.jhep.2022.06.018openalex-snapshot
Digital pathology with artificial intelligence analyses provides greater insights into treatment-induced fibrosis regression in NASH
inferred← citeshttps://doi.org/10.1016/j.jhepr.2022.100443openalex-snapshot
Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
inferred← citeshttps://doi.org/10.1016/j.jpi.2024.100372openalex-snapshot
Quantitative digital pathology enables automated and quantitative assessment of inflammatory activity in patients with autoimmune hepatitis
inferred← citeshttps://doi.org/10.1016/j.jpi.2024.100416openalex-snapshot
Liver fibrosis classification on trichrome histology slides using weakly supervised learning in children and young adults
inferred← citeshttps://doi.org/10.1016/j.jpi.2026.100656openalex-snapshot
Detection of macrovesicular steatosis in hematoxylin and eosin-stained histological images of human livers: A feature-based method
inferred← citeshttps://doi.org/10.1016/j.labinv.2023.100223openalex-snapshot
Quantitative Assessment of Hepatic Steatosis Using Label-Free Multiphoton Imaging and Customized Image Processing Program
inferred← citeshttps://doi.org/10.1016/j.landig.2026.101017openalex-snapshot
Digital pathology, image analysis, and artificial intelligence in liver disease
inferred← citeshttps://doi.org/10.1016/j.liver.2026.100318openalex-snapshot
Deep learning for non-invasive NAFLD detection and staging: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.modpat.2023.100377openalex-snapshot
An End-to-End Platform for Digital Pathology Using Hyperspectral Autofluorescence Microscopy and Deep Learning-Based Virtual Histology
inferred← citeshttps://doi.org/10.1016/j.patter.2020.100080openalex-snapshot
A Distance-Based Framework for the Characterization of Metabolic Heterogeneity in Large Sets of Genome-Scale Metabolic Models
inferred← citeshttps://doi.org/10.1017/s2633903x23000144openalex-snapshot
Fibrosis severity scoring on Sirius red histology with multiple-instance deep learning
inferred← citeshttps://doi.org/10.1038/s41575-023-00843-7openalex-snapshot
Digital pathology for nonalcoholic steatohepatitis assessment
inferred← citeshttps://doi.org/10.1038/s41575-024-00955-8openalex-snapshot
A roadmap for clinical trials in MASH-related compensated cirrhosis
inferred← citeshttps://doi.org/10.1038/s41591-022-01853-9openalex-snapshot
Omics and AI advance biomarker discovery for liver disease
inferred← citeshttps://doi.org/10.1038/s41598-022-15364-7openalex-snapshot
Multimodal NASH prognosis using 3D imaging flow cytometry and artificial intelligence to characterize liver cells
inferred← citeshttps://doi.org/10.1038/s41598-022-22902-wopenalex-snapshot
Automated whole slide image analysis for a translational quantification of liver fibrosis
inferred← citeshttps://doi.org/10.1038/s41598-023-44897-8openalex-snapshot
Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury
inferred← citeshttps://doi.org/10.1038/s41598-024-63095-8openalex-snapshot
A machine learning-based model analysis for serum markers of liver fibrosis in chronic hepatitis B patients
inferred← citeshttps://doi.org/10.1038/s41598-025-09288-1openalex-snapshot
Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease
inferred← citeshttps://doi.org/10.1039/d3an00324hopenalex-snapshot
Enhancing the accuracy of mid-infrared spectroscopy-based liver steatosis quantification using digital image analysis as a reference
inferred← citeshttps://doi.org/10.1053/j.semdp.2022.01.003openalex-snapshot
Artificial intelligence for dermatopathology: Current trends and the road ahead
inferred← citeshttps://doi.org/10.1055/a-2599-3728openalex-snapshot
Big Data Analytics in Large Cohorts: Opportunities and Challenges for Research in Hepatology
inferred← citeshttps://doi.org/10.1055/s-0041-1731706openalex-snapshot
Artificial Intelligence in Hepatology: A Narrative Review
inferred← citeshttps://doi.org/10.1063/5.0133327openalex-snapshot
A descriptive study of fatty liver disease detection using machine learning
inferred← citeshttps://doi.org/10.1080/10255842.2023.2217978openalex-snapshot
Estimation of non-alcoholic steatohepatitis (NASH) disease using clinical information based on the optimal combination of intelligent algorithms for feature selection and classification
inferred← citeshttps://doi.org/10.1080/21678707.2022.2131393openalex-snapshot
Recommendations for overcoming challenges in the diagnosis of lysosomal acid lipase deficiency
inferred← citeshttps://doi.org/10.1080/23808993.2022.2053285openalex-snapshot
Non-alcoholic fatty liver disease - opportunities for personalized treatment and drug development
inferred← citeshttps://doi.org/10.1097/hep.0000000000000866openalex-snapshot
Digital pathology and spatial omics in steatohepatitis: Clinical applications and discovery potentials
inferred← citeshttps://doi.org/10.1097/hep.0000000000000967openalex-snapshot
Is digital pathology the new standard in MASH trials?
inferred← citeshttps://doi.org/10.1097/hep.0000000000001811openalex-snapshot
Decoding fibrosis: Transcriptomic and clinical insights via AI-derived collagen deposition phenotypes in MASLD
inferred← citeshttps://doi.org/10.1097/pap.0000000000000483openalex-snapshot
Steatotic Liver Disease: Navigating Pathologic Features, Diagnostic Challenges, and Emerging Insights
inferred← citeshttps://doi.org/10.1097/txd.0000000000001361openalex-snapshot
A Novel Digital Algorithm for Identifying Liver Steatosis Using Smartphone-Captured Images
inferred← citeshttps://doi.org/10.1101/2022.09.02.22279476openalex-snapshot
The future of computational pathology: expectations regarding the anticipated role of artificial intelligence in pathology by 2030
inferred← citeshttps://doi.org/10.1109/icbar55169.2021.00038openalex-snapshot
Research progress of artificial intelligence in the diagnosis of fatty liver
inferred← citeshttps://doi.org/10.1109/icet56601.2022.10004660openalex-snapshot
Predictive analysis on severity of Non-Alcoholic Fatty Liver Disease (NAFLD) using Machine Learning Algorithms
inferred← citeshttps://doi.org/10.1109/jbhi.2025.3556709openalex-snapshot
BSMatch: Boundary Segmentation and Matching for Lipid Droplet Quantification in Diagnosis of Non-Alcoholic Fatty Liver Disease
inferred← citeshttps://doi.org/10.1109/ojemb.2024.3379479openalex-snapshot
Lymphocyte-Infiltrated Periportal Region Detection With Structurally-Refined Deep Portal Segmentation and Heterogeneous Infiltration Features
inferred← citeshttps://doi.org/10.1111/apm.70236openalex-snapshot
No Sex Differences in the Amount of Type IV Collagen in Wistar Rats Regardless of Sampling Strategy
inferred← citeshttps://doi.org/10.1111/apt.17456openalex-snapshot
Review article: The need for more efficient and patient‐oriented drug development pathways in NASH—setting the scene for platform trials
inferred← citeshttps://doi.org/10.1111/jgh.15385openalex-snapshot
Artificial intelligence in prediction of non‐alcoholic fatty liver disease and fibrosis
inferred← citeshttps://doi.org/10.1111/jgh.15415openalex-snapshot
Artificial intelligence in precision medicine in hepatology
inferred← citeshttps://doi.org/10.1111/jgh.15843openalex-snapshot
Reliability of the nonalcoholic steatohepatitis clinical research network and steatosis activity fibrosis histological scoring systems
inferred← citeshttps://doi.org/10.1111/liv.15571openalex-snapshot
Hepatocytic ballooning in non‐alcoholic steatohepatitis: Dilemmas and future directions
inferred← citeshttps://doi.org/10.1111/liv.15799openalex-snapshot
Object detection: A novel AI technology for the diagnosis of hepatocyte ballooning
inferred← citeshttps://doi.org/10.1111/liv.70194openalex-snapshot
Digital Histopathology and AI : A New Era of Liver Fibrosis Quantification
inferred← citeshttps://doi.org/10.1136/flgastro-2024-102705openalex-snapshot
Metabolic-associated steatotic liver disease (MASLD): how I evolved my approach to diagnosis and staging
inferred← citeshttps://doi.org/10.1136/gutjnl-2020-323202openalex-snapshot
From the origin of NASH to the future of metabolic fatty liver disease
inferred← citeshttps://doi.org/10.1136/gutjnl-2021-326874openalex-snapshot
Current therapies and new developments in NASH
inferred← citeshttps://doi.org/10.1136/jcp-2022-208614openalex-snapshot
Survey of liver pathologists to assess attitudes towards digital pathology and artificial intelligence
inferred← citeshttps://doi.org/10.1136/jcp-2025-210311openalex-snapshot
AI portal tract detection and characterisation for a regional analysis of steatosis and inflammation in MASLD, MASH and AIH
inferred← citeshttps://doi.org/10.1148/radiol.2021211027openalex-snapshot
Automated Whole-Liver MRI Segmentation to Assess Steatosis and Iron Quantification in Chronic Liver Disease
inferred← citeshttps://doi.org/10.1177/10556656251347366openalex-snapshot
Quantifying Sagittal Craniosynostosis Severity: A Machine Learning Approach With CranioRate
inferred← citeshttps://doi.org/10.1371/journal.pone.0278580openalex-snapshot
Age-dependent sex difference of non-alcoholic fatty liver disease in TSOD and db/db mice
inferred← citeshttps://doi.org/10.15403/jgld-4180openalex-snapshot
A Primer into the Current State of Artificial Intelligence in Gastroenterology
inferred← citeshttps://doi.org/10.21037/qims-22-393openalex-snapshot
The spectrum of magnetic resonance imaging proton density fat fraction (MRI-PDFF), magnetic resonance spectroscopy (MRS), and two different histopathologic methods (artificial intelligence vs. pathologist) in quantifying hepatic steatosis
inferred← citeshttps://doi.org/10.2196/preprints.46914openalex-snapshot
The global research of artificial intelligence on metabolic dysfunction-associated fatty liver disease: a bibliometric analysis (Preprint)
inferred← citeshttps://doi.org/10.24963/ijcai.2022/220openalex-snapshot
Learning Sparse Interpretable Features For NAS Scoring From Liver Biopsy Images
inferred← citeshttps://doi.org/10.3138/canlivj-2021-0030openalex-snapshot
Current considerations for clinical management and care of non-alcoholic fatty liver disease: Insights from the 1st International Workshop of the Canadian NASH Network (CanNASH)
inferred← citeshttps://doi.org/10.3350/cmh.2020.0181openalex-snapshot
Updates in the quantitative assessment of liver fibrosis for nonalcoholic fatty liver disease: Histological perspective
inferred← citeshttps://doi.org/10.3350/cmh.2022.0329openalex-snapshot
Non-alcoholic fatty liver disease: the pathologist’s perspective
inferred← citeshttps://doi.org/10.3389/fmed.2022.925357openalex-snapshot
Developing a New qFIBS Model Assessing Histological Features in Pediatric Patients With Non-alcoholic Steatohepatitis
inferred← citeshttps://doi.org/10.3389/fmed.2024.1480866openalex-snapshot
Role of artificial intelligence in staging and assessing of treatment response in MASH patients
inferred← citeshttps://doi.org/10.3389/ti.2022.10640openalex-snapshot
Artificial Intelligence: Present and Future Potential for Solid Organ Transplantation
inferred← citeshttps://doi.org/10.3390/biom11121808openalex-snapshot
Digital Pathology Enables Automated and Quantitative Assessment of Inflammatory Activity in Patients with Chronic Liver Disease
inferred← citeshttps://doi.org/10.3390/biomedicines13040846openalex-snapshot
Digital Pathology Tailored for Assessment of Liver Biopsies
inferred← citeshttps://doi.org/10.3390/cancers15102791openalex-snapshot
A Paradigm Shift in Primary Liver Cancer Therapy Utilizing Genomics, Molecular Biomarkers, and Artificial Intelligence
inferred← citeshttps://doi.org/10.3390/diagnostics11061078openalex-snapshot
Non-Alcoholic Fatty Liver Disease: Implementing Complete Automated Diagnosis and Staging. A Systematic Review
inferred← citeshttps://doi.org/10.3390/diagnostics13101799openalex-snapshot
Artificial Intelligence-Based Opportunities in Liver Pathology—A Systematic Review
inferred← citeshttps://doi.org/10.3390/diagnostics16162533openalex-snapshot
Applying Artificial Intelligence to Childhood Obesity: T2DM and MASLD Risk Predictive Models
inferred← citeshttps://doi.org/10.3390/healthcare11010117openalex-snapshot
Artificial Intelligence in NAFLD: Will Liver Biopsy Still Be Necessary in the Future?
inferred← citeshttps://doi.org/10.3390/ijms27177825openalex-snapshot
From Molecular Mechanisms to Clinical Strategies: A Comprehensive Overview of Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
inferred← citeshttps://doi.org/10.3390/info13040160openalex-snapshot
Ensemble Convolutional Neural Network Classification for Pancreatic Steatosis Assessment in Biopsy Images
inferred← citeshttps://doi.org/10.3390/jcm11082265openalex-snapshot
Clinical Applications of Artificial Intelligence—An Updated Overview
inferred← citeshttps://doi.org/10.3390/jcm12155072openalex-snapshot
Biased Quantification of Rat Liver Fibrosis—Meta-Analysis with Practical Recommendations and Clinical Implications
inferred← citeshttps://doi.org/10.3390/jcm14176231openalex-snapshot
Diagnostic Applications of Artificial Intelligence in Liver Diseases
inferred← citeshttps://doi.org/10.3390/s21061993openalex-snapshot
Efficiency of Machine Learning Algorithms for the Determination of Macrovesicular Steatosis in Frozen Sections Stained with Sudan to Evaluate the Quality of the Graft in Liver Transplantation
inferred← citeshttps://doi.org/10.35712/aig.v3.i2.46openalex-snapshot
Application of artificial intelligence in non-alcoholic fatty liver disease and viral hepatitis
inferred← citeshttps://doi.org/10.36469/001c.123645openalex-snapshot
Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis
inferred← citeshttps://doi.org/10.36469/jheor.2024.123645openalex-snapshot
Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis
inferred← citeshttps://doi.org/10.3748/wjg.v27.i16.1664openalex-snapshot
Artificial intelligence in gastroenterology and hepatology: Status and challenges
inferred← citeshttps://doi.org/10.3748/wjg.v27.i20.2545openalex-snapshot
State of machine and deep learning in histopathological applications in digestive diseases
inferred← citeshttps://doi.org/10.3748/wjg.v27.i40.6794openalex-snapshot
Artificial intelligence in gastroenterology: A state-of-the-art review
inferred← citeshttps://doi.org/10.3748/wjg.v28.i46.6551openalex-snapshot
Hybrid XGBoost model with hyperparameter tuning for prediction of liver disease with better accuracy
inferred← citeshttps://doi.org/10.3748/wjg.v32.i2.111737openalex-snapshot
Artificial intelligence in metabolic dysfunction-associated steatotic liver disease: Transforming diagnosis and therapeutic approaches
inferred← citeshttps://doi.org/10.4103/ijpm.ijpm_947_20openalex-snapshot
Liver biopsy in the quantitative assessment of liver fibrosis in nonalcoholic fatty liver disease
inferred← citeshttps://doi.org/10.4254/wjh.v13.i10.1417openalex-snapshot
Machine learning models for predicting non-alcoholic fatty liver disease in the general United States population: NHANES database
inferred← citeshttps://doi.org/10.4254/wjh.v18.i1.112821openalex-snapshot
Evaluation methods of hepatic steatosis: From conventional techniques to emerging biomarkers
inferred← citeshttps://doi.org/10.5114/aoms/140451openalex-snapshot
Association between Cluster of Differentiation 24 (CD24) Polymorphism, Talin-1 gene expression and Hepatocellular Carcinoma prevalence in Egyptian population
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.