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Graft Rejection

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Usefulness of Delayed Introduction of Tacrolimus in Kidney Transplants Using Type-III Donors After Circulatory Death.

Transplantation proceedings
INTRODUCTION: Our study compares 2 immunosuppressive strategies to reduce tacrolimus nephrotoxicity and its risk of acute tubular necrosis: delayed introduction of tacrolimus plus thymoglobulin vs initial tacrolimus plus basiliximab on the results of...

Results of a Literature Review to Prepare Data Modelling in the Context of Kidney Transplant Rejection Diagnosis.

Studies in health technology and informatics
Due to demographic change the number of serious kidney diseases and thus required transplantations will increase. The increased demand for donor organs and a decreasing supply of these organs underline the necessity for effective early rejection diag...

An integrated molecular diagnostic report for heart transplant biopsies using an ensemble of diagnostic algorithms.

The Journal of heart and lung transplantation : the official publication of the International Society for Heart Transplantation
BACKGROUND: We previously reported a microarray-based diagnostic system for heart transplant endomyocardial biopsies (EMBs), using either 3-archetype (3AA) or 4-archetype (4AA) unsupervised algorithms to estimate rejection. In the present study we ex...

A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides.

Scientific reports
Pathologic diagnoses mainly depend on visual scoring by pathologists, a process that can be time-consuming, laborious, and susceptible to inter- and/or intra-observer variations. This study proposes a novel method to enhance pathologic scoring of ren...

Generating automated kidney transplant biopsy reports combining molecular measurements with ensembles of machine learning classifiers.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons
We previously reported a system for assessing rejection in kidney transplant biopsies using microarray-based gene expression data, the Molecular Microscope Diagnostic System (MMDx). The present study was designed to optimize the accuracy and stabilit...

Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.

International journal of medical informatics
INTRODUCTION: Machine learning has been increasingly used to develop predictive models to diagnose different disease conditions. The heterogeneity of the kidney transplant population makes predicting graft outcomes extremely challenging. Several kidn...

Graft Rejection Prediction Following Kidney Transplantation Using Machine Learning Techniques: A Systematic Review and Meta-Analysis.

Studies in health technology and informatics
Kidney transplantation is recommended for patients with End-Stage Renal Disease (ESRD). However, complications, such as graft rejection are hard to predict due to donor and recipient variability. This study discusses the role of machine learning (ML)...

Automated detection algorithm for C4d immunostaining showed comparable diagnostic performance to pathologists in renal allograft biopsy.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
A deep learning-based image analysis could improve diagnostic accuracy and efficiency in pathology work. Recently, we proposed a deep learning-based detection algorithm for C4d immunostaining in renal allografts. The objective of this study is to ass...