Training of computational algorithms to predict NAFLD activity score and fibrosis stage from liver histopathology slides

H Qu, CD Minacapelli, C Tait, K Gupta… - Computer Methods and …, 2021 - Elsevier
Background The incidence of non-alcoholic fatty liver disease (NAFLD) and its progressive
form, non-alcoholic steatohepatitis (NASH), has been increasing for decades. Since the …

Deep learning enables pathologist-like scoring of NASH models

F Heinemann, G Birk, B Stierstorfer - Scientific reports, 2019 - nature.com
Non-alcoholic fatty liver disease (NAFLD) and the progressive form of non-alcoholic
steatohepatitis (NASH) are diseases of major importance with a high unmet medical need …

Deep learning-based quantification of NAFLD/NASH progression in human liver biopsies

F Heinemann, P Gross, S Zeveleva, HS Qian, J Hill… - Scientific Reports, 2022 - nature.com
Non-alcoholic fatty liver disease (NAFLD) affects about 24% of the world's population.
Progression of early stages of NAFLD can lead to the more advanced form non-alcoholic …

An unsupervised transfer learning model based on convolutional auto encoder for non-alcoholic steatohepatitis activity scoring and fibrosis staging of liver …

MA Karagoz, B Akay, A Basturk, D Karaboga… - Neural Computing and …, 2023 - Springer
Non-alcoholic fatty liver disease (NAFLD) is one of the most frequent chronic liver diseases
worldwide. Non-alcoholic steatohepatitis (NASH) is a progressive type of NAFLD that may …

Deep learning based NAS Score and fibrosis stage prediction from CT and pathology data

A Jana, H Qu, P Rattan, CD Minacapelli… - 2020 IEEE 20th …, 2020 - ieeexplore.ieee.org
Non-Alcoholic Fatty Liver Disease (NAFLD) is becoming increasingly prevalent in the world
population. Without diagnosis at the right time, NAFLD can lead to non-alcoholic …

Artificial intelligence and deep learning: New tools for histopathological diagnosis of nonalcoholic fatty liver disease/nonalcoholic steatohepatitis

Y Takahashi, E Dungubat, H Kusano… - Computational and …, 2023 - Elsevier
Nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) is associated
with metabolic syndrome and is rapidly increasing globally with the increased prevalence of …

[HTML][HTML] High-throughput, machine learning–based quantification of steatosis, inflammation, ballooning, and fibrosis in biopsies from patients with nonalcoholic fatty …

R Forlano, BH Mullish, N Giannakeas… - Clinical …, 2020 - Elsevier
Background & Aims Liver biopsy is the reference standard for staging and grading
nonalcoholic fatty liver disease (NAFLD), but histologic scoring systems are semiquantitative …

Machine learning to predict progression of non‐alcoholic fatty liver to non‐alcoholic steatohepatitis or fibrosis

S Ghandian, R Thapa, A Garikipati, G Barnes… - JGH …, 2022 - Wiley Online Library
Background Non‐alcoholic fatty liver (NAFL) can progress to the severe subtype non‐
alcoholic steatohepatitis (NASH) and/or fibrosis, which are associated with increased …

A Machine Learning Method to Identify the Risk Factors for Liver Fibrosis Progression in Nonalcoholic Steatohepatitis

M Suárez, R Martínez, AM Torres, B Torres… - Digestive Diseases and …, 2023 - Springer
Aim Nonalcoholic fatty liver disease (NAFLD) is a silent epidemy that has become the most
common chronic liver disease worldwide. Nonalcoholic steatohepatitis (NASH) is an …

Machine learning approaches for early detection of non-alcoholic steatohepatitis based on clinical and blood parameters

AR Naderi Yaghouti, H Zamanian, A Shalbaf - Scientific Reports, 2024 - nature.com
This study aims to develop a machine learning approach leveraging clinical data and blood
parameters to predict non-alcoholic steatohepatitis (NASH) based on the NAFLD Activity …