AIMC Topic: Fibrosis
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A deep learning framework for personalised dynamic diagnosis of graft fibrosis after liver transplantation: a retrospective, single Canadian centre, longitudinal study.
The Lancet. Digital health
May 18, 2023
BACKGROUND: Recurrent graft fibrosis after liver transplantation can threaten both graft and patient survival. Therefore, early detection of fibrosis is essential to avoid disease progression and the need for retransplantation. Non-invasive blood-bas...
Quantitative assessment of myocardial fibrosis by digital image analysis: An adjunctive tool for pathologist "ground truth".
Cardiovascular pathology : the official journal of the Society for Cardiovascular Pathology
Apr 29, 2023
AIMS: Myocardial fibrosis (MF) is a common pathological process in a wide range of cardiovascular diseases. Its quantity has diagnostic and prognostic relevance. We aimed to assess if the complementary use of an automated artificial intelligence soft...
Prognostic value of deep learning-based fibrosis quantification on chest CT in idiopathic pulmonary fibrosis.
European radiology
Mar 16, 2023
OBJECTIVE: To investigate the prognostic value of deep learning (DL)-driven CT fibrosis quantification in idiopathic pulmonary fibrosis (IPF).
Nonalcoholic fatty liver disease (NAFLD) detection and deep learning in a Chinese community-based population.
European radiology
Mar 9, 2023
OBJECTIVES: We aimed to develop and validate a deep learning system (DLS) by using an auxiliary section that extracts and outputs specific ultrasound diagnostic features to improve the explainable, clinical relevant utility of using DLS for detecting...
Deep-learning algorithm to detect fibrosing interstitial lung disease on chest radiographs.
The European respiratory journal
Feb 16, 2023
BACKGROUND: Antifibrotic therapies are available to treat chronic fibrosing interstitial lung diseases (CF-ILDs), including idiopathic pulmonary fibrosis. Early use of these treatments is recommended to slow deterioration of respiratory function and ...
Deep learning-based quantification of NAFLD/NASH progression in human liver biopsies.
Scientific reports
Nov 10, 2022
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 steatohepatitis (NASH), and ultimately to cirrhosis or liver cancer. The curr...
Deep learning-based quantitative estimation of lymphedema-induced fibrosis using three-dimensional computed tomography images.
Scientific reports
Sep 13, 2022
In lymphedema, proinflammatory cytokine-mediated progressive cascades always occur, leading to macroscopic fibrosis. However, no methods are practically available for measuring lymphedema-induced fibrosis before its deterioration. Technically, CT can...
Intestinal fibrosis classification in patients with Crohn's disease using CT enterography-based deep learning: comparisons with radiomics and radiologists.
European radiology
May 26, 2022
OBJECTIVES: Accurate evaluation of bowel fibrosis in patients with Crohn's disease (CD) remains challenging. Computed tomography enterography (CTE)-based radiomics enables the assessment of bowel fibrosis; however, it has some deficiencies. We aimed ...
Very low-volume interval training improves nonalcoholic fatty liver disease fibrosis score and cardiometabolic health in adults with obesity and metabolic syndrome.
Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
Apr 24, 2022
Non-alcoholic fatty liver disease (NAFLD) and cardiometabolic disorders are highly prevalent in obese individuals. Physical exercise is an important element in obesity and metabolic syndrome (MetS) treatment. However, the vast majority of individuals...
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