AIMC Topic: Renal Insufficiency, Chronic

Clear Filters Showing 211 to 220 of 262 articles

Personalized Prediction of Chronic Kidney Disease Progression in Patients with Chronic Kidney Disease Stages 3-5: A Multicenter Study Using the Machine Learning Approach.

Studies in health technology and informatics
Chronic Kidney Disease (CKD) is a prevalent and progressive condition that can lead to end-stage renal disease (ESRD) if left unmanaged. Accurate prediction of CKD progression, particularly in patients with CKD stages 3-5, is essential for early inte...

Deep learning for early detection of chronic kidney disease stages in diabetes patients: A TabNet approach.

Artificial intelligence in medicine
Chronic kidney disease (CKD) poses a significant risk for diabetes patients, often leading to severe complications. Early and accurate CKD stage detection is crucial for timely intervention. However, it remains challenging due to its asymptomatic pro...

Label-free urinary protein detection through machine learning analysis of single droplet evaporation patterns.

Analytica chimica acta
BACKGROUND: Chronic kidney disease (CKD) is a major global public health issue, with a steadily increasing incidence. Urinary protein detection serves as a crucial indicator for the diagnosis, monitoring and management of CKD. However, current method...

Identification and validation of inflammatory response genes linking chronic kidney disease with coronary artery disease based on bioinformatics and machine learning.

Scientific reports
Coronary artery disease (CAD) commonly occurs and elevates the risk of cardiovascular events and mortality in chronic kidney disease (CKD) patients. The underlying pathogenesis of CKD-related CAD is believed to be closely linked to inflammatory respo...

Model Systems of Chronic Kidney Disease: A Detailed Overview and Recent Advances.

Journal of biochemical and molecular toxicology
Experimental model systems, especially animal models, are indispensable tools to study human diseases and to develop new therapeutics. Chronic kidney disease (CKD) is a major global health problem having significantly higher rate of morbidity and mor...

MSMTSeg: Multi-Stained Multi-Tissue Segmentation of Kidney Histology Images via Generative Self-Supervised Meta-Learning Framework.

IEEE journal of biomedical and health informatics
Accurately diagnosing chronic kidney disease requires pathologists to assess the structure of multiple tissues under different stains, a process that is time-consuming and labor-intensive. Current AI-based methods for automatic structure assessment, ...

Improved CKD classification based on explainable artificial intelligence with extra trees and BBFS.

Scientific reports
Chronic kidney disease is a persistent ailment marked by the gradual decline of kidney function. Its classification primarily relies on the estimated glomerular filtration rate and the existence of kidney damage. The kidney disease improving global o...

Balancing accuracy and cost in machine learning models for detecting medial vascular calcification in chronic kidney disease: a pilot study.

Scientific reports
Machine learning algorithms that integrate multiple biomarkers are increasingly used in disease detection, yet economic considerations are often overlooked. Medial vascular calcification (mVC), a pathology associated with elevated cardiovascular risk...

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...