AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Renal Insufficiency, Chronic

Showing 31 to 40 of 218 articles

Clear Filters

Development of a machine learning tool to predict the risk of incident chronic kidney disease using health examination data.

Frontiers in public health
BACKGROUND: Chronic kidney disease (CKD) is characterized by a decreased glomerular filtration rate or renal injury (especially proteinuria) for at least 3 months. The early detection and treatment of CKD, a major global public health concern, before...

Identification and optimization of relevant factors for chronic kidney disease in abdominal obesity patients by machine learning methods: insights from NHANES 2005-2018.

Lipids in health and disease
BACKGROUND: The intake of dietary antioxidants and glycolipid metabolism are closely related to chronic kidney disease (CKD), particularly among individuals with abdominal obesity. Nevertheless, the cumulative effect of multiple comorbid risk factors...

Machine learning approaches for predicting and diagnosing chronic kidney disease: current trends, challenges, solutions, and future directions.

International urology and nephrology
Chronic Kidney Disease (CKD) represents a significant global health challenge, contributing to increased morbidity and mortality rates. This review paper explores the current landscape of machine learning (ML) techniques employed in CKD prediction an...

Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.

Scientific reports
The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general po...

Interpretable Deep-learning Model Based on Superb Microvascular Imaging for Noninvasive Diagnosis of Interstitial Fibrosis in Chronic Kidney Disease.

Academic radiology
RATIONALE AND OBJECTIVES: To develop an interpretable deep learning (XDL) model based on superb microvascular imaging (SMI) for the noninvasive diagnosis of the degree of interstitial fibrosis (IF) in chronic kidney disease (CKD).

Artificial intelligence in predicting chronic kidney disease prognosis. A systematic review and meta-analysis.

Renal failure
BACKGROUND: Chronic kidney disease (CKD) is a common condition that can lead to serious health complications. Artificial Intelligence (AI) has shown the potential to improve the prediction of CKD progression, offering increased accuracy over traditio...

Predicting the risk of chronic kidney disease based on uric acid concentration in stones using biosensors integrated with a deep learning-based ANN system.

Talanta
Elevated levels of uric acid (UA) in the body may not only lead to the formation of stones but also increase the risk of developing chronic kidney disease (CKD). This study presents a biosensor for detecting UA concentration in stones and a deep lear...

Unraveling Uncertainty: The Impact of Biological and Analytical Variation on the Prediction Uncertainty of Categorical Prediction Models.

The journal of applied laboratory medicine
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...

An artificial intelligence-based gout management system reduced chronic kidney disease incident and improved target serum urate achievement.

Rheumatology (Oxford, England)
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...