AIMC Topic: Kidney Transplantation

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Artificial intelligence-driven kidney organ allocation: systematic review of clinical outcome prediction, ethical frameworks, and decision-making algorithms.

BMC nephrology
Kidney transplantation remains the optimal treatment for end-stage renal disease, yet persistent organ shortages and inequitable allocation necessitate innovative solutions. Artificial intelligence (AI) and machine learning (ML) have emerged as promi...

Immune cell quantification of in situ inflammation partitions human lupus nephritis into mechanistic subtypes.

The Journal of clinical investigation
BACKGROUNDIn human lupus nephritis (LuN), tubulointerstitial inflammation (TII) is prognostically more important than glomerular inflammation. However, a comprehensive understanding of both TII complexity and heterogeneity is lacking.METHODSHerein, w...

Integrated single-cell and clinical transcriptomic analysis identifies blunted glycolytic activation as a hallmark of maladaptive repair in renal ischemia-reperfusion.

Renal failure
Acute kidney injury (AKI) is a common and increases risk of chronic kidney disease (CKD). While mitochondrial dysfunction drives maladaptive repair, the role of glycolysis in renal recovery remains unclear. Here, we integrated single-cell transcripto...

Comparative analysis of outcomes in high KDPI spectrum kidney transplants using unsupervised machine learning algorithm.

PloS one
BACKGROUND: The Kidney Donor Profile Index (KDPI) is a continuous metric used to estimate the risk of allograft failure for kidneys from deceased donors. Lower KDPI scores are associated with longer post-transplant kidney function. This study aims to...

Prediction of the risk of transplant rejection based on RNA sequencing data of PBMCs before transplantation.

Scientific reports
Novel methods for detecting transplant rejection are craved, since conventional methods can detect ongoing rejection that may sometimes have already caused irreversible damage in transplanted organs. Here, we applied a transcriptomics database of rec...

A novel method to predict the haemoglobin concentration after kidney transplantation based on machine learning: prediction model establishment and method optimization.

BMC medical informatics and decision making
BACKGROUND: Anaemia is a common complication after kidney transplantation, and the haemoglobin concentration is one of the main criteria for identifying anaemia. Moreover, artificial intelligence methods have developed rapidly in recent years, are wi...

Prediction of postoperative infection through early-stage salivary microbiota following kidney transplantation using machine learning techniques.

Renal failure
Kidney transplantation (KT) is an effective treatment for end-stage renal disease; however, the lifelong immunosuppressive regimen increases the risk of infection, presenting significant clinical, and economic challenges. Identifying predictive bioma...

Personalized prediction model generated with machine learning for kidney function one year after living kidney donation.

Scientific reports
Living kidney donors typically experience approximately a 30% reduction in kidney function after donation, although the degree of reduction varies among individuals. This study aimed to develop a machine learning (ML) model to predict serum creatinin...