AI Medical Compendium Journal:
Kidney diseases (Basel, Switzerland)

Showing 1 to 10 of 14 articles

Longitudinal Follow-Up and Outcomes for Chinese Patients with Stage 1-4 Chronic Kidney Disease.

Kidney diseases (Basel, Switzerland)
INTRODUCTION: Understanding heterogeneity in the prognosis of chronic kidney disease (CKD) has implications in management of patients. We aimed to evaluate the comparative risk of end-stage kidney disease (ESKD), cardiovascular (CV) events, and death...

Hyperuricemia and Impaired Renal Function: A Prospective Cohort Study.

Kidney diseases (Basel, Switzerland)
BACKGROUND: Related studies have demonstrated a relationship of elevated serum uric levels with a decline in kidney function. However, limited evidence exists in a Southeast Asian community-based population.

Incorporation of Urinary Neutrophil Gelatinase-Associated Lipocalin and Computed Tomography Quantification to Predict Acute Kidney Injury and In-Hospital Death in COVID-19 Patients.

Kidney diseases (Basel, Switzerland)
BACKGROUND: The prevalence of acute kidney injury (AKI) in COVID-19 patients is high, with poor prognosis. Early identification of COVID-19 patients who are at risk for AKI and may develop critical illness and death is of great importance.

Artificial Intelligence in Nephrology: How Can Artificial Intelligence Augment Nephrologists' Intelligence?

Kidney diseases (Basel, Switzerland)
BACKGROUND: Artificial intelligence (AI) now plays a critical role in almost every area of our daily lives and academic disciplines due to the growth of computing power, advances in methods and techniques, and the explosion of the amount of data; med...

Progression of Metabolic Acidosis in Chronic Kidney Disease.

Kidney diseases (Basel, Switzerland)
BACKGROUND: Metabolic acidosis, which is classified into either high anion gap type (high-AGMA) or non-anion gap type (non-AGMA), is a common complication in chronic kidney disease (CKD), but its development in CKD is obscure.

Safety and Efficacy of Tolvaptan for the Prevention of Contrast-Induced Acute Kidney Injury in Patients with Heart Failure and Chronic Kidney Disease.

Kidney diseases (Basel, Switzerland)
BACKGROUND: Tolvaptan is a promising drug for the prevention of contrast-induced acute kidney injury (CI-AKI) because it induces aquaresis without adversely affecting renal hemodynamics. CI-AKI is a major cause of acute renal failure associated with ...

Individual and Combined Relationship between Reduced eGFR and/or Increased Urinary Albumin Excretion Rate with Mortality Risk among Insulin-Treated Patients with Type 2 Diabetes in Routine Practice.

Kidney diseases (Basel, Switzerland)
BACKGROUND: A low estimated glomerular filtration rate (eGFR) and an increased urinary albumin-to-creatinine ratio (ACR) are well-recognised prognostic markers of cardiovascular (CV) risk, but their individual and combined relationship with CV diseas...

Development of an Artificial Intelligence Model to Guide the Management of Blood Pressure, Fluid Volume, and Dialysis Dose in End-Stage Kidney Disease Patients: Proof of Concept and First Clinical Assessment.

Kidney diseases (Basel, Switzerland)
BACKGROUND: Fluid volume and blood pressure (BP) management are crucial endpoints for end-stage kidney disease patients. BP control in clinical practice mainly relies on reducing extracellular fluid volume overload by diminishing targeted postdialysi...

Blood Pressure Assessment with Differential Pulse Transit Time and Deep Learning: A Proof of Concept.

Kidney diseases (Basel, Switzerland)
BACKGROUND: Modern clinical environments are laden with technology devices continuously gathering physiological data from patients. This is especially true in critical care environments, where life-saving decisions may have to be made on the basis of...

Deep Reinforcement Learning in Medicine.

Kidney diseases (Basel, Switzerland)
Reinforcement learning has achieved tremendous success in recent years, notably in complex games such as Atari, Go, and chess. In large part, this success has been made possible by powerful function approximation methods in the form of deep neural ne...