AIMC Topic: Renal Dialysis
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Prediction of Arteriovenous Access Dysfunction by Mel Spectrogram-based Deep Learning Model.
International journal of medical sciences
Aug 19, 2024
The early detection of arteriovenous (AV) access dysfunction is crucial for maintaining the patency of vascular access. This study aimed to use deep learning to predict AV access malfunction necessitating further vascular management. This prospecti...
The application of blood flow sound contrastive learning to predict arteriovenous graft stenosis of patients with hemodialysis.
PloS one
Aug 16, 2024
End-stage kidney disease (ESKD) presents a significant public health challenge, with hemodialysis (HD) remaining one of the most prevalent kidney replacement therapies. Ensuring the longevity and functionality of arteriovenous accesses is challenging...
Construction of Risk-Prediction Models for Autogenous Arteriovenous Fistula Thrombosis in Patients on Maintenance Hemodialysis.
Blood purification
Aug 1, 2024
INTRODUCTION: Autogenous arteriovenous fistula (AVF) is the preferred vascular access in patients undergoing maintenance hemodialysis (MHD). However, complications such as thrombosis may occur. This study aimed to construct and validate a machine lea...
Predictive approach for liberation from acute dialysis in ICU patients using interpretable machine learning.
Scientific reports
Jun 7, 2024
Renal recovery following dialysis-requiring acute kidney injury (AKI-D) is a vital clinical outcome in critical care, yet it remains an understudied area. This retrospective cohort study, conducted in a medical center in Taiwan from 2015 to 2020, enr...
Safety and Efficacy of Acute Central Venous Catheters for Hemodialysis with Sodium Bicarbonate versus an Antibiotic Catheter Locking Solution.
Saudi journal of kidney diseases and transplantation : an official publication of the Saudi Center for Organ Transplantation, Saudi Arabia
May 9, 2024
This study was conducted to determine the safety and efficacy of acute central venous catheters (CVC) using a sodium bicarbonate catheter locking solution (SBCLS) versus an antibiotic catheter locking solution (ACLS). Our study included patients aged...
The relationship between satisfaction with life, dietary attitude, and comfort level in hemodialysis patients: Analysis with machine learning approach.
Therapeutic apheresis and dialysis : official peer-reviewed journal of the International Society for Apheresis, the Japanese Society for Apheresis, the Japanese Society for Dialysis Therapy
May 1, 2024
INTRODUCTION: Hemodialysis (HD) patients have become a serious public health problem, the number of which is increasing every year worldwide. This study aimed to determine the relationship between satisfaction with life, dietary attitude, and comfort...
Personalised prediction of maintenance dialysis initiation in patients with chronic kidney disease stages 3-5: a multicentre study using the machine learning approach.
BMJ health & care informatics
Apr 27, 2024
BACKGROUND: Optimal timing for initiating maintenance dialysis in patients with chronic kidney disease (CKD) stages 3-5 is challenging. This study aimed to develop and validate a machine learning (ML) model for early personalised prediction of mainte...
A systematic review of prediction models on arteriovenous fistula: Risk scores and machine learning approaches.
The journal of vascular access
Apr 24, 2024
OBJECTIVE: Failure-to-mature and early stenosis remains the Achille's heel of hemodialysis arteriovenous fistula (AVF) creation. The maturation and patency of an AVF can be influenced by a variety of demographic, comorbidity, and anatomical factors. ...
Reproducibility of Results
Risk Factors
Aged
Male
Machine Learning
Humans
Treatment Outcome
Middle Aged
Decision Support Techniques
Arteriovenous Shunt, Surgical
Risk Assessment
Predictive Value of Tests
Clinical Decision-Making
Graft Occlusion, Vascular
Renal Dialysis
Female
Vascular Patency
Time Factors
Deep learning algorithms for predicting renal replacement therapy initiation in CKD patients: a retrospective cohort study.
BMC nephrology
Mar 14, 2024
BACKGROUND: Chronic kidney disease (CKD) requires accurate prediction of renal replacement therapy (RRT) initiation risk. This study developed deep learning algorithms (DLAs) to predict RRT risk in CKD patients by incorporating medical history and pr...
DeepVAQ : an adaptive deep learning for prediction of vascular access quality in hemodialysis patients.
BMC medical informatics and decision making
Feb 12, 2024
BACKGROUND: Chronic kidney disease is a prevalent global health issue, particularly in advanced stages requiring dialysis. Vascular access (VA) quality is crucial for the well-being of hemodialysis (HD) patients, ensuring optimal blood transfer throu...
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