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Fibrosis

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Development of a Radiomics-Based Model to Predict Graft Fibrosis in Liver Transplant Recipients: A Pilot Study.

Transplant international : official journal of the European Society for Organ Transplantation
Liver Transplantation is complicated by recurrent fibrosis in 40% of recipients. We evaluated the ability of clinical and radiomic features to flag patients at risk of developing future graft fibrosis. CT scans of 254 patients at 3-6 months post-live...

Integrating inflammatory biomarker analysis and artificial-intelligence-enabled image-based profiling to identify drug targets for intestinal fibrosis.

Cell chemical biology
Intestinal fibrosis, often caused by inflammatory bowel disease, can lead to intestinal stenosis and obstruction, but there are no approved treatments. Drug discovery has been hindered by the lack of screenable cellular phenotypes. To address this, w...

Artificial intelligence-assisted repurposing of lubiprostone alleviates tubulointerstitial fibrosis.

Translational research : the journal of laboratory and clinical medicine
Tubulointerstitial fibrosis (TIF) is the most prominent cause which leads to chronic kidney disease (CKD) and end-stage renal failure. Despite extensive research, there have been many clinical trial failures, and there is currently no effective treat...

Using Artificial Intelligence to Predict Cirrhosis From Computed Tomography Scans.

Clinical and translational gastroenterology
INTRODUCTION: Undiagnosed cirrhosis remains a significant problem. In this study, we developed and tested an automated liver segmentation tool to predict the presence of cirrhosis in a population of patients with paired liver biopsy and computed tomo...

A large-scale retrospective study enabled deep-learning based pathological assessment of frozen procurement kidney biopsies to predict graft loss and guide organ utilization.

Kidney international
Lesion scores on procurement donor biopsies are commonly used to guide organ utilization for deceased-donor kidneys. However, frozen sections present challenges for histological scoring, leading to inter- and intra-observer variability and inappropri...

Suitability of machine learning for atrophy and fibrosis development in neovascular age-related macular degeneration.

Acta ophthalmologica
PURPOSE: To assess the suitability of machine learning (ML) techniques in predicting the development of fibrosis and atrophy in patients with neovascular age-related macular degeneration (nAMD), receiving anti-VEGF treatment over a 36-month period.

Point-of-care diagnosis of tissue fibrosis: a review of advances in vibrational spectroscopy with machine learning.

Pathology
Histopathology is the gold standard for diagnosing fibrosis, but its routine use is constrained by the need for additional stains, time, personnel and resources. Vibrational spectroscopy is a novel technique that offers an alternative atraumatic appr...

Strong Diagnostic Performance of Single Energy 256-row Multidetector Computed Tomography with Deep Learning Image Reconstruction in the Assessment of Myocardial Fibrosis.

Internal medicine (Tokyo, Japan)
Objective Although magnetic resonance imaging (MRI) is the gold standard for evaluating abnormal myocardial fibrosis and extracellular volume (ECV) of the left ventricular myocardium (LVM), a similar evaluation has recently become possible using comp...

Interpretable machine learning model integrating clinical and elastosonographic features to detect renal fibrosis in Asian patients with chronic kidney disease.

Journal of nephrology
BACKGROUND: Non-invasive renal fibrosis assessment is critical for tailoring personalized decision-making and managing follow-up in patients with chronic kidney disease (CKD). We aimed to exploit machine learning algorithms using clinical and elastos...