AIMC Topic: Renal Insufficiency, Chronic
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An artificial intelligence-based gout management system reduced chronic kidney disease incident and improved target serum urate achievement.
Rheumatology (Oxford, England)
May 1, 2025
OBJECTIVES: Stage ≥3 chronic kidney disease (CKD) affects ∼25% of people with gout. The effects of urate-lowering therapy (ULT) on CKD incidence and progression have remained inconclusive. Here, we assessed the impact of a gout ULT clinic interventio...
Unraveling Uncertainty: The Impact of Biological and Analytical Variation on the Prediction Uncertainty of Categorical Prediction Models.
The journal of applied laboratory medicine
Mar 3, 2025
BACKGROUND: Interest in prediction models, including machine learning (ML) models, based on laboratory data has increased tremendously. Uncertainty in laboratory measurements and predictions based on such data are inherently intertwined. This study d...
Artificial Intelligence to Predict Chronic Kidney Disease Progression to Kidney Failure: A Narrative Review.
Nephrology (Carlton, Vic.)
Jan 1, 2025
Chronic kidney disease is characterised by the progressive loss of kidney function. However, predicting who will progress to kidney failure is difficult. Artificial Intelligence, including Machine Learning, shows promise in this area. This narrative ...
A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction.
Briefings in bioinformatics
Nov 22, 2024
Artificial intelligence (AI)-based multi-modal fusion algorithms are pivotal in emulating clinical practice by integrating data from diverse sources. However, most of the existing multi-modal models focus on designing new modal fusion methods, ignori...
TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.
Journal of the American Medical Informatics Association : JAMIA
Nov 1, 2024
OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision mana...
Application of Artificial Intelligence in Clinical Practice - Perception of a Multinational Group of Nephrologists.
Studies in health technology and informatics
Aug 22, 2024
This study investigates the perception of a multinational group of nephrologists on artificial intelligence (AI) application in clinical practice. A validated on-line survey was performed in March 2024, in 4 continents. The results revealed a prevale...
Learning Enabled Control for Optimal EPO Dosage in Virtual CKD Patients: Case of Bleeding and Missing Dosage.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Traditional model-based control methods require predictive models to design control policies. These models often suffer limitations on dimensionality, uncertainty, and unmodeled dynamics. This affects the performance of control policy, especially, pe...
Ensemble Learning Approaches for Automatic Detection of Chronic Kidney Disease Stages during Sleep.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
This study investigates the use of ensemble learning methods for the automatic detection of chronic kidney disease (CKD) stages during sleep. We applied and evaluated four ensemble learning approaches-CatBoost, random forest, XGBoost, and LightGBM-to...
Towards early detection of chronic kidney disease based on gait patterns: IMU-based approach using neural networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
The aging population has led to an increased prevalence of chronic kidney disease (CKD), associated with a higher incidence of gait disturbances and rise in fall rates. It is important that early detection and continuous monitoring of CKD to improve ...
Deep Learning-Based Assessment of Built Environment From Satellite Images and Cardiometabolic Disease Prevalence.
JAMA cardiology
Jun 1, 2024
IMPORTANCE: Built environment plays an important role in development of cardiovascular disease. Large scale, pragmatic evaluation of built environment has been limited owing to scarce data and inconsistent data quality.
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