AIMC Topic: Graft Rejection
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Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.
PloS one
Nov 27, 2024
BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to the vulnerability of aged donor kidneys to ischemic damage, delayed graft function, and reduced graft ...
Machine learning methods to identify risk factors for corneal graft rejection in keratoconus.
Scientific reports
Nov 25, 2024
Machine learning can be used to identify risk factors associated with graft rejection after corneal transplantation for keratoconus. The study included all keratoconus eyes that underwent primary corneal transplantation from 1994 to 2021. Data relati...
[Pathology of transplanted heart rejection using artificial intelligence-based image analysis of endomyocardial biopsies].
Orvosi hetilap
Nov 3, 2024
Predicting graft survival in paediatric kidney transplant recipients using machine learning.
Pediatric nephrology (Berlin, Germany)
Aug 16, 2024
BACKGROUND: Identification of factors that affect graft survival in kidney transplantation can increase graft survival and reduce mortality. Artificial intelligence modelling enables impartial evaluation of clinician bias. This study aimed to examine...
APOD: A biomarker associated with oxidative stress in acute rejection of kidney transplants based on multiple machine learning algorithms and animal experimental validation.
Transplant immunology
Aug 2, 2024
BACKGROUND: Oxidative stress is an unavoidable process in kidney transplantation and is closely related to the development of acute rejection after kidney transplantation. This study aimed to investigate the biomarkers associated with oxidative stres...
Predicting graft and patient outcomes following kidney transplantation using interpretable machine learning models.
Scientific reports
Jul 29, 2024
The decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretabl...
Deep learning-enabled classification of kidney allograft rejection on whole slide histopathologic images.
Frontiers in immunology
Jul 5, 2024
BACKGROUND: Diagnosis of kidney transplant rejection currently relies on manual histopathological assessment, which is subjective and susceptible to inter-observer variability, leading to limited reproducibility. We aim to develop a deep learning sys...
Diagnosis and classification of kidney transplant rejection using machine learning-assisted surface-enhanced Raman spectroscopy using a single drop of serum.
Biosensors & bioelectronics
Jun 24, 2024
The quest to reduce kidney transplant rejection has emphasized the urgent requirement for the development of non-invasive, precise diagnostic technologies. These technologies aim to detect antibody-mediated rejection (ABMR) and T-cell-mediated reject...
Predicting Success in Descemet Membrane Endothelial Keratoplasty Using Machine Learning.
Cornea
Jun 20, 2024
PURPOSE: This study aimed to predict early graft failure (GF) in patients who underwent Descemet membrane endothelial keratoplasty based on donor characteristics.
Predicting kidney allograft survival with explainable machine learning.
Transplant immunology
May 24, 2024
INTRODUCTION: Despite significant progress over the last decades in the survival of kidney allografts, several risk factors remain contributing to worsening kidney function or even loss of transplants. We aimed to evaluate a new machine learning meth...
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