AIMC Topic: Fibrosis
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Quantifying Fibrosis in Fibrotic Lung Disease: A Good Human Plus a Machine Is the Best Combination?
Annals of the American Thoracic Society
Feb 1, 2024
Deep learning for assessing liver fibrosis based on acoustic nonlinearity maps: an in vivo study of rabbits.
Computer assisted surgery (Abingdon, England)
Dec 1, 2022
This study aimed to assess liver fibrosis in rabbits by deep learning models based on acoustic nonlinearity maps. Injection of carbon tetrachloride was used to induce liver fibrosis. Acoustic nonlinearity maps, which were built by data of echo signal...
End-to-end interstitial fibrosis assessment of kidney biopsies with a machine learning-based model.
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Oct 19, 2022
BACKGROUND: The extent of interstitial fibrosis in the kidney not only correlates with renal function at the time of biopsy but also predicts future renal outcome. However, its assessment by pathologists lacks good agreement. The aim of this study is...
Development and validation of an ensemble machine learning framework for detection of all-cause advanced hepatic fibrosis: a retrospective cohort study.
The Lancet. Digital health
Mar 1, 2022
BACKGROUND: Cirrhosis is the result of advanced scarring (or fibrosis) of the liver, and is often diagnosed once decompensation with associated complications has occurred. Current non-invasive tests to detect advanced liver fibrosis have limited perf...
[Early Assessment of Myocardial Fibrosis of Hypertrophic Cardiomyopathy with Native-T1-Mapping-Based Deep Learning: A Preliminary Study].
Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition
Sep 1, 2021
OBJECTIVE: To explore the diagnostic performance of deep learning (DL) model in early detection of the interstitial myocardial fibrosis using native T1 maps of hypertrophic cardiomyopathy (HCM) without late gadolinium enhancement (LGE).
Classifying Microscopic Acute and Old Myocardial Infarction Using Convolutional Neural Networks.
The American journal of forensic medicine and pathology
Sep 1, 2021
Convolutional neural network (CNN) has advanced in recent years and translated from research into medical practice, most notably in clinical radiology and histopathology. Research on CNNs in forensic/postmortem pathology is almost exclusive to postmo...
Dr AFC: drug repositioning through anti-fibrosis characteristic.
Briefings in bioinformatics
May 20, 2021
Fibrosis is a key component in the pathogenic mechanism of a variety of diseases. These diseases involving fibrosis may share common mechanisms and therapeutic targets, and therefore common intervention strategies and medicines may be applicable for ...
Radiomics and deep learning in liver diseases.
Journal of gastroenterology and hepatology
Mar 1, 2021
Recently, radiomics and deep learning have gained attention as methods for computerized image analysis. Radiomics and deep learning can perform diagnostic or predictive tasks using high-dimensional image-derived features and have the potential to exp...
aqueous extract attenuates isoproterenol-induced cardiac hypertrophy through the ERK signalling pathway.
Pharmaceutical biology
Dec 1, 2020
CONTEXT: The pharmacological functions of Wall. ex Lindl. (Orchidaceae) in cardiac hypertrophy remains unclear.
Automated Measurements of Muscle Mass Using Deep Learning Can Predict Clinical Outcomes in Patients With Liver Disease.
The American journal of gastroenterology
Aug 1, 2020
INTRODUCTION: There is increasing recognition of the central role of muscle mass in predicting clinical outcomes in patients with liver disease. Muscle size can be extracted from computed tomography (CT) scans, but clinical implementation will requir...
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