AIMC Topic: Primary Graft Dysfunction

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Developing approaches to incorporate donor-lung computed tomography images into machine learning models to predict severe primary graft dysfunction after lung transplantation.

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons Feb 7, 2025
Primary graft dysfunction (PGD) is a common complication after lung transplantation associated with poor outcomes. Although risk factors have been identified, the complex interactions between clinical variables affecting PGD risk are not well underst...
Graft Survival Follow-Up Studies Lung Transplantation Primary Graft Dysfunction Middle Aged Tissue Donors Adult Male Prognosis Retrospective Studies Female Risk Factors Tomography, X-Ray Computed Humans Machine Learning
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Machine learning analysis of contrast-enhanced ultrasound (CEUS) for the diagnosis of acute graft dysfunction in kidney transplant recipients.

Medical ultrasonography Sep 4, 2024
AIM: The aim of the study was to develop machine learning algorithms (MLA) for diagnosing acute graft dysfunction (AGD) in kidney transplant recipients based on contrast-enhanced ultrasound (CEUS) analysis of the graft.Materials and methods: This pro...
Ultrasonography Kidney Contrast Media Acute Disease Middle Aged Machine Learning Sensitivity and Specificity Image Enhancement Reproducibility of Results Humans Kidney Transplantation Male Primary Graft Dysfunction Postoperative Complications Adult Prospective Studies Female
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AI finally provides augmented intelligence to liver surgeons.

EBioMedicine Oct 20, 2020
Fatty Liver Primary Graft Dysfunction Liver Surgeons Biopsy Humans Deep Learning Liver Transplantation Artificial Intelligence
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Predicting Primary Graft Dysfunction in Systemic Sclerosis Lung Transplantation Using Machine-Learning and CT Features.

Clinical transplantation Jul 1, 2025
INTRODUCTION: Primary graft dysfunction (PGD) is a significant barrier to survival in lung transplant (LTx) recipients. PGD in patients with systemic sclerosis (SSc) remains especially underrepresented in research.
Prognosis Retrospective Studies Humans Machine Learning Risk Factors Adult Tomography, X-Ray Computed Female Lung Transplantation Graft Survival Scleroderma, Systemic Follow-Up Studies Primary Graft Dysfunction Male Middle Aged
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Discover important donor-recipient risk factors and interactions in heart transplant primary graft dysfunction with machine learning.

Journal of the American Medical Informatics Association : JAMIA Jul 1, 2025
OBJECTIVES: Primary graft dysfunction (PGD) is an essential outcome after the heart transplant, which causes severe complications and symptoms for recipients. The in advance prediction of PGD can help the transplant physician better manage the risks ...
Female Risk Factors Humans Machine Learning Algorithms ROC Curve Heart Transplantation Tissue Donors Primary Graft Dysfunction Transplant Recipients
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