AIMC Topic: Kidney Transplantation
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Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA sequencing and molecular docking.
Renal failure
Dec 4, 2024
Post-transplant allograft fibrosis remains a challenge in prolonging allograft survival. Regulated cell death has been widely implicated in various kidney diseases, including renal fibrosis. However, the role of different regulated cell death (RCD) ...
Deciphering the impact of senescence in kidney transplant rejection: An integrative machine learning and multi-omics analysis via bulk and single-cell RNA sequencing.
PloS one
Nov 27, 2024
BACKGROUND: The demographic shift towards an older population presents significant challenges for kidney transplantation (KTx), particularly due to the vulnerability of aged donor kidneys to ischemic damage, delayed graft function, and reduced graft ...
AI-assisted patient education: Challenges and solutions in pediatric kidney transplantation.
Patient education and counseling
Nov 26, 2024
We are writing in response to the recent publication on the use of artificial intelligence, particularly ChatGPT, in generating educational materials for pediatric kidney transplant patients (Patient Education and Counseling, Volume 129, 2024). The s...
Predicting the risk of pulmonary infection after kidney transplantation using machine learning methods: a retrospective cohort study.
International urology and nephrology
Nov 2, 2024
PURPOSE: Pulmonary infection is the most common and serious complication after kidney transplantation that affects the survival of the transplanted kidney and the quality of life of patients. This study aims to construct a machine learning model for ...
The role of artificial intelligence measured preoperative kidney volume in predicting kidney function loss in elderly kidney donors: a multicenter cohort study.
International journal of surgery (London, England)
Nov 1, 2024
BACKGROUND: The increasing use of kidneys from elderly donors raises concerns due to age-related nephron loss. Combined with nephrectomy, this loss of nephrons markedly increases the risk of developing chronic kidney disease (CKD). This study aimed t...
Predicting prognostic factors in kidney transplantation using a machine learning approach to enhance outcome predictions: a retrospective cohort study.
International journal of surgery (London, England)
Nov 1, 2024
BACKGROUND: Accurate forecasting of clinical outcomes after kidney transplantation is essential for improving patient care and increasing the success rates of transplants. The authors' study employs advanced machine learning (ML) algorithms to identi...
Improved survival prediction for kidney transplant outcomes using artificial intelligence-based models: development of the UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool.
Renal failure
Oct 22, 2024
The UK Deceased Donor Kidney Transplant Outcome Prediction (UK-DTOP) Tool, developed using advanced artificial intelligence (AI), significantly enhances the prediction of outcomes for deceased-donor kidney transplants in the UK. This study analyzed d...
An integrated machine learning model enhances delayed graft function prediction in pediatric renal transplantation from deceased donors.
BMC medicine
Sep 20, 2024
BACKGROUND: Kidney transplantation is the optimal renal replacement therapy for children with end-stage renal disease; however, delayed graft function (DGF), a common post-operative complication, may negatively impact the long-term outcomes of both t...
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...
Predicting graft survival in paediatric kidney transplant recipients using machine learning.
Pediatric nephrology (Berlin, Germany)
Aug 16, 2024
BACKGROUND: Identification of factors that affect graft survival in kidney transplantation can increase graft survival and reduce mortality. Artificial intelligence modelling enables impartial evaluation of clinician bias. This study aimed to examine...
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