AIMC Topic: Graft Rejection
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Automated evaluation with deep learning of total interstitial inflammation and peritubular capillaritis on kidney biopsies.
Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association
Nov 30, 2023
BACKGROUND: Interstitial inflammation and peritubular capillaritis are observed in many diseases on native and transplant kidney biopsies. A precise and automated evaluation of these histological criteria could help stratify patients' kidney prognose...
Toward Improved and Standardized Diagnostic Pipelines in Transplantation.
Transplantation
Jan 1, 2021
Graft Rejection Prediction Following Kidney Transplantation Using Machine Learning Techniques: A Systematic Review and Meta-Analysis.
Studies in health technology and informatics
Aug 21, 2019
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)...
Liver and Lung Transplant Advances.
JAMA
Mar 12, 2019
Using Deep Learning in Automated Detection of Graft Detachment in Descemet Membrane Endothelial Keratoplasty: A Pilot Study.
Cornea
Feb 1, 2019
PURPOSE: To evaluate a deep learning-based method to automatically detect graft detachment (GD) after Descemet membrane endothelial keratoplasty (DMEK) in anterior segment optical coherence tomography (AS-OCT).
Results of a Literature Review to Prepare Data Modelling in the Context of Kidney Transplant Rejection Diagnosis.
Studies in health technology and informatics
Jan 1, 2019
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...
Integrative Analysis of Proteomics Data to Obtain Clinically Relevant Markers.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2018
The analysis of proteomics data can be significantly challenging. Beyond the technical challenges of accurately identifying and quantifying peptides, identifying the most biologically coherent set of biomarkers can be a particularly daunting step. In...
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