AIMC Topic: Renal Dialysis

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Artificial intelligence supported anemia control system (AISACS) to prevent anemia in maintenance hemodialysis patients.

International journal of medical sciences Feb 22, 2021
Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as preventive measures, presents important difficulties for hemodialysis patients. Nevertheless, the number of physicians able to manage such medications a...
Electronic Health Records Female Aged Aged, 80 and over Humans Machine Learning Retrospective Studies Decision Support Systems, Clinical Iron Kidney Failure, Chronic Hemoglobins Anemia Adult Male Middle Aged Renal Dialysis Datasets as Topic Hematinics
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Leveraging Deep Learning to Improve Safety of Outpatient Hemodialysis.

Clinical journal of the American Society of Nephrology : CJASN Feb 11, 2021
Humans Deep Learning Renal Dialysis Outpatients
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Deep Learning Model for Real-Time Prediction of Intradialytic Hypotension.

Clinical journal of the American Society of Nephrology : CJASN Feb 11, 2021
BACKGROUND AND OBJECTIVES: Intradialytic hypotension has high clinical significance. However, predicting it using conventional statistical models may be difficult because several factors have interactive and complex effects on the risk. Herein, we ap...
Humans Forecasting Retrospective Studies Female Renal Dialysis Computer Systems Models, Theoretical Hypotension Random Allocation Aged Male Middle Aged Deep Learning
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Assessing Dry Weight of Hemodialysis Patients via Sparse Laplacian Regularized RVFL Neural Network with L-Norm.

BioMed research international Feb 4, 2021
Dry weight is the normal weight of hemodialysis patients after hemodialysis. If the amount of water in diabetes is too much (during hemodialysis), the patient will experience hypotension and shock symptoms. Therefore, the correct assessment of the pa...
Male Machine Learning Middle Aged Female Renal Dialysis Aged Body Mass Index Adult Models, Statistical Humans Blood Pressure Neural Networks, Computer Body Weight Body Weights and Measures
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Prediction of outcomes after acute kidney injury in hospitalised patients: protocol for a systematic review.

BMJ open Dec 22, 2020
INTRODUCTION: Acute kidney injury (AKI) is common and is associated with negative long-term outcomes. Given the heterogeneity of the syndrome, the ability to predict outcomes of AKI may be beneficial towards effectively using resources and personalis...
Meta-Analysis as Topic Humans Artificial Intelligence Acute Kidney Injury Adult Renal Dialysis Systematic Reviews as Topic
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Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

Clinical journal of the American Society of Nephrology : CJASN Oct 8, 2020
BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records.
Simplified Acute Physiology Score Glutamyl Aminopeptidase Creatinine L-Lactate Dehydrogenase Alanine Transaminase Bilirubin Lactic Acid Liver Diseases Blood Urea Nitrogen Leukocyte Count Female Aged Male Middle Aged Databases, Factual Sepsis Prognosis Renal Dialysis Acute Kidney Injury United States Electronic Health Records Comorbidity Deep Learning Humans Phenotype
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Evaluation of Hemodialysis Arteriovenous Bruit by Deep Learning.

Sensors (Basel, Switzerland) Aug 27, 2020
Physical findings of auscultation cannot be quantified at the arteriovenous fistula examination site during daily dialysis treatment. Consequently, minute changes over time cannot be recorded based only on subjective observations. In this study, we s...
Female Aged Aged, 80 and over Male Middle Aged Deep Learning Renal Dialysis ROC Curve Humans Neural Networks, Computer Auscultation Arteriovenous Fistula
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Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

BioMed research international Jun 10, 2020
BACKGROUND: The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medi...
Kidney Failure, Chronic Decision Making, Computer-Assisted Quality of Life Humans Renal Dialysis Artificial Intelligence Models, Statistical Algorithms Graft Rejection Kidney Transplantation
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Application of explainable ensemble artificial intelligence model to categorization of hemodialysis-patient and treatment using nationwide-real-world data in Japan.

PloS one May 29, 2020
BACKGROUND: Although dialysis patients are at a high risk of death, it is difficult for medical practitioners to simultaneously evaluate many inter-related risk factors. In this study, we evaluated the characteristics of hemodialysis patients using m...
Adult Male Middle Aged Deep Learning Female Risk Factors Aged Aged, 80 and over Cluster Analysis Renal Dialysis Cohort Studies Logistic Models Kidney Failure, Chronic Support Vector Machine Japan Machine Learning Humans Decision Making, Computer-Assisted Artificial Intelligence Databases, Factual Prospective Studies Prognosis
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Predictive modeling of blood pressure during hemodialysis: a comparison of linear model, random forest, support vector regression, XGBoost, LASSO regression and ensemble method.

Computer methods and programs in biomedicine May 22, 2020
BACKGROUND: Intradialytic hypotension (IDH) is commonly occurred and links to higher mortality among patients undergoing hemodialysis (HD). Its early prediction and prevention will dramatically improve the quality of life. However, predicting the occ...
Blood Pressure Humans Linear Models Machine Learning Algorithms Quality of Life Renal Dialysis
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