AIMC Topic: Kidney Transplantation

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Prediction of delayed graft function after kidney transplantation: comparison between logistic regression and machine learning methods.

BMC medical informatics and decision making
BACKGROUND: Predictive models for delayed graft function (DGF) after kidney transplantation are usually developed using logistic regression. We want to evaluate the value of machine learning methods in the prediction of DGF.

Robotic-assisted kidney transplantation: our first case.

World journal of urology
PURPOSE: Kidney transplantation is the preferred treatment for patients with end-stage renal disease. In order to reduce the morbidity of the open surgery, a robotic-assisted approach has been recently introduced. According to the published literatur...

Prediction of peripheral blood lymphocyte subpopulations after renal transplantation.

Renal failure
Immune monitoring is essential for maintaining immune homeostasis after renal transplantation (RT). Peripheral blood lymphocyte subpopulations (PBLSs) are widely used biomarkers for immune monitoring, yet there is no established standard reference fo...

Artificial intelligence in kidney transplantation: a 30-year bibliometric analysis of research trends, innovations, and future directions.

Renal failure
Kidney transplantation is the definitive treatment for end-stage renal disease (ESRD), yet challenges persist in optimizing donor-recipient matching, postoperative care, and immunosuppressive strategies. This study employs bibliometric analysis to ev...

Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool.

Renal failure
Predicting the outcome of a kidney transplant involving a living donor advances donor decision-making donors for clinicians and patients. However, the discriminative or calibration capacity of the currently employed models are limited. We set out to...

Renal Transplant Survival Prediction From Unsupervised Deep Learning-Based Radiomics on Early Dynamic Contrast-Enhanced MRI.

Academic radiology
RATIONALE AND OBJECTIVES: End-stage renal disease is characterized by an irreversible decline in kidney function. Despite a risk of chronic dysfunction of the transplanted kidney, renal transplantation is considered the most effective solution among ...

Development and Validation of Ultrasound Hemodynamic-based Prediction Models for Acute Kidney Injury After Renal Transplantation.

Academic radiology
RATIONALE AND OBJECTIVES: Acute kidney injury (AKI) post-renal transplantation often has a poor prognosis. This study aimed to identify patients with elevated risks of AKI after kidney transplantation.

Multiple omics-based machine learning reveals specific macrophage sub-clusters in renal ischemia-reperfusion injury and constructs predictive models for transplant outcomes.

Computational biology and chemistry
BACKGROUND: Ischemia-reperfusion injury (IRI) is closely associated with numerous severe postoperative complications, including acute rejection, delayed graft function (DGF) and graft failure. Macrophages are central to modulating the aseptic inflamm...