AIMC Topic: Graft Rejection
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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
Mar 26, 2020
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...
Using machine learning techniques to develop risk prediction models to predict graft failure following kidney transplantation: protocol for a retrospective cohort study.
F1000Research
Oct 29, 2019
A mechanism to predict graft failure before the actual kidney transplantation occurs is crucial to clinical management of chronic kidney disease patients. Several kidney graft outcome prediction models, developed using machine learning methods, are...
Machine learning in predicting graft failure following kidney transplantation: A systematic review of published predictive models.
International journal of medical informatics
Aug 24, 2019
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...
A Novel CNN-Based CAD System for Early Assessment of Transplanted Kidney Dysfunction.
Scientific reports
Apr 11, 2019
This paper introduces a deep-learning based computer-aided diagnostic (CAD) system for the early detection of acute renal transplant rejection. For noninvasive detection of kidney rejection at an early stage, the proposed CAD system is based on the f...
Postoperative Complications
Diagnosis, Computer-Assisted
Adolescent
Graft Survival
Glomerular Filtration Rate
Young Adult
Adult
Male
Middle Aged
Kidney Function Tests
Follow-Up Studies
Graft Rejection
Image Interpretation, Computer-Assisted
Diffusion Magnetic Resonance Imaging
Humans
Neural Networks, Computer
Algorithms
Kidney Transplantation
Prognosis
Female
Risk Factors
Aged
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
Apr 10, 2019
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...
A Fully Automated System Using A Convolutional Neural Network to Predict Renal Allograft Rejection: Extra-validation with Giga-pixel Immunostained Slides.
Scientific reports
Mar 26, 2019
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...
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
Feb 6, 2019
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...
Usefulness of Delayed Introduction of Tacrolimus in Kidney Transplants Using Type-III Donors After Circulatory Death.
Transplantation proceedings
Oct 29, 2018
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...
The future is coming: promising perspectives regarding the use of machine learning in renal transplantation.
Jornal brasileiro de nefrologia
Oct 18, 2018
INTRODUCTION: The prediction of post transplantation outcomes is clinically important and involves several problems. The current prediction models based on standard statistics are very complex, difficult to validate and do not provide accurate predic...
Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.
Clinical transplantation
Oct 15, 2018
The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely obese have shown minimal complication, long-term outcomes are understudied. Previously, we reported no...
United States
Treatment Outcome
Glomerular Filtration Rate
Kidney Function Tests
Follow-Up Studies
Robotics
Graft Rejection
Minimally Invasive Surgical Procedures
Kidney Failure, Chronic
Survival Rate
Obesity, Morbid
Male
Kidney Transplantation
Middle Aged
Prognosis
Humans
Time Factors
Female
Graft Survival
Risk Factors
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