AIMC Topic: Graft Rejection
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Effect of the vascularized bone components on the survival of vascularized composite allografts.
The Journal of surgical research
Apr 6, 2017
BACKGROUND: Vascularized composite allograft (VCA), such as hand and face allograft, contains a vascularized bone component that may provide an immunologic benefit and induce tolerance for the simultaneous inclusion of marrow cells and a marrow micro...
High soluble CD30 levels and associated anti-HLA antibodies in patients with failed renal allografts.
The International journal of artificial organs
Dec 26, 2016
INTRODUCTION: Serum soluble CD30 (sCD30), a 120-kD glycoprotein that belongs to the tumor necrosis factor receptor family, has been suggested as a marker of rejection in kidney transplant patients. The aim of this study was to evaluate the relationsh...
Re: Robotic Trans-Abdominal Transplant Nephrectomy for a Failed Renal Allograft.
The Journal of urology
Apr 8, 2015
Deep learning-based histopathologic segmentation of peritubular capillaries in kidney transplant biopsies.
Computers in biology and medicine
Jul 1, 2025
BACKGROUND: Assessing the extent of inflammation in peritubular capillaries (PTCs) is important for diagnosing antibody-mediated rejection in kidney transplant biopsies. However, this assessment is time-consuming and suffers from interobserver variab...
Artificial intelligence-enhanced interpretation of kidney transplant biopsy: focus on rejection.
Current opinion in organ transplantation
Jun 1, 2025
PURPOSE OF REVIEW: The objective of this review is to provide an update on the application of artificial intelligence (AI) for the histological interpretation of kidney transplant biopsies.
GraftIQ: Hybrid multi-class neural network integrating clinical insight for multi-outcome prediction in liver transplant recipients.
Nature communications
May 28, 2025
Liver transplant recipients (LTRs) are at risk of graft injury, leading to cirrhosis and reduced survival. Liver biopsy, the diagnostic gold standard, is invasive and risky. We developed a hybrid multi-class neural network (NN) model, 'GraftIQ,' inte...
On the Harmonisation of Time Series Data for the Optimisation of Machine Learning Using the Example of Rejection Prediction After Kidney Transplantation.
Studies in health technology and informatics
May 15, 2025
A significant risk following a kidney transplantation is graft loss. The Screen Reject Project has developed a Clinical Data Warehouse (CDWH) as a foundation for a clinical decision support system designed to improve the diagnosis of graft rejections...
Utilizing Machine Learning to Predict Liver Allograft Fibrosis by Leveraging Clinical and Imaging Data.
Clinical transplantation
Apr 1, 2025
BACKGROUND AND AIM: Liver transplant (LT) recipients may succumb to graft-related pathologies, contributing to graft fibrosis (GF). Current methods to diagnose GF are limited, ranging from procedural-related complications to low accuracy. With recent...
Identifying Risk Factors for Graft Failure due to Chronic Rejection < 15 Years Post-Transplant in Pediatric Kidney Transplants Using Random Forest Machine-Learning Techniques.
Pediatric transplantation
Mar 1, 2025
BACKGROUND: Chronic rejection forms the leading cause of late graft loss in pediatric kidney transplant recipients. Despite improvement in short-term graft outcomes, chronic rejection impedes comparable progress in long-term graft outcomes.
Detection and classification of glomerular lesions in kidney graft biopsies using 2-stage deep learning approach.
Medicine
Feb 14, 2025
Acute allograft rejection in patients undergoing renal transplantation is diagnosed through histopathological analysis of renal graft biopsies, which can be used to quantify elementary lesions. However, quantification of elementary lesions requires c...
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