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Related Concept Videos

Chronic Kidney Disease I: Introduction01:25

Chronic Kidney Disease I: Introduction

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Chronic Kidney Disease (CKD) arises when the kidneys progressively lose their ability to function, ultimately leading to end-stage kidney disease (ESKD). At this advanced stage, the kidneys can no longer filter waste or maintain essential body functions, requiring renal replacement therapy (RRT) through dialysis or a kidney transplant for survival.Early-stage chronic kidney disease and detection challengesIn CKD's early stages, symptoms often remain absent because healthy nephrons compensate...
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Chronic Kidney Disease III: Interprofessional Care01:28

Chronic Kidney Disease III: Interprofessional Care

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Chronic kidney disease (CKD) requires collaborative and comprehensive management. CKD progresses through stages and can lead to end-stage kidney disease (ESKD) if untreated. Interprofessional collaboration and patient education are crucial, enabling patients to manage their health and improve their quality of life.Diagnostic approach for chronic kidney diseaseThe diagnosis of CKD primarily focuses on the glomerular filtration rate (GFR), which assesses kidney function by measuring how well...
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Chronic Kidney Disease II: Clinical Manifestations01:24

Chronic Kidney Disease II: Clinical Manifestations

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Chronic Kidney Disease (CKD) progressively impairs multiple body systems due to the accumulation of uremic toxins, which disrupt cellular functions across various organs.Neurologic symptomsNeurologic symptoms often arise early in CKD, as uremic toxin buildup drives changes in cognitive and motor functions. Patients frequently experience fatigue, headache, confusion, difficulty concentrating, and, in severe cases, seizures. Peripheral neuropathy commonly manifests as burning sensations in the...
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Acute Kidney Injury IV: Diagnostic Studies and Prevention01:30

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Accurate diagnosis and effective prevention are critical in managing Acute Kidney Injury (AKI), which is linked to high mortality rates ranging from 10% to 80%. Timely recognition of at-risk patients and careful monitoring can significantly reduce the likelihood of kidney damage.Diagnostic Assessments:The diagnostic process starts with a comprehensive medical history to identify prerenal, intrarenal, and postrenal causes.Prerenal causes, such as dehydration, hypotension, or blood loss, should...
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Nephrons01:10

Nephrons

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The kidneys are intricate organs with millions of working units known as nephrons. Each nephron features two major structures: the renal corpuscle, which facilitates blood plasma filtration, and the renal tubule, which handles the glomerular filtrate. Blood supply is directly linked to the nephrons. The renal corpuscle consists of the glomerulus, a capillary network, and the Bowman's capsule, a double-walled epithelial structure that encases the glomerulus. The filtering of blood plasma...
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Acute Kidney Injury I: Introduction01:22

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Introduction:Acute Kidney Injury (AKI) describes a swift decrease in kidney function occurring over hours to days, characterized by the kidneys' failure to remove waste products from the bloodstream. This leads to dangerous complications like metabolic acidosis, fluid overload, and electrolyte imbalances, such as hyperkalemia, which can cause life-threatening arrhythmias. AKI is common in both hospital and outpatient settings, often triggered by dehydration, sepsis, or exposure to nephrotoxic...
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Snake-Efficient Feature Selection-Based Framework for Precise Early Detection of Chronic Kidney Disease.

Walaa N Ismail1

  • 1Department of Management Information Systems, College of Business Administration, Al Yamamah University, Riyadh 11512, Saudi Arabia.

Diagnostics (Basel, Switzerland)
|August 12, 2023
PubMed
Summary

A new snake optimization (SO) framework accurately detects chronic kidney disease (CKD) using machine learning. This method achieves 99.7% accuracy, enabling early intervention and reducing mortality.

Keywords:
chronic kidney diseaseconvolution neural networksdeep neural networkfeature selectionmachine learningmedical data analysissnake optimization

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Area of Science:

  • Nephrology
  • Artificial Intelligence
  • Bioinformatics

Background:

  • Chronic kidney disease (CKD) is a progressive condition requiring early detection for effective management.
  • Manual screening for CKD is labor-intensive and prone to subjective errors.
  • Machine learning (ML) and feature selection offer automated solutions for early CKD detection.

Purpose of the Study:

  • To develop a novel snake-optimized (SO) framework, named CKD-SO, for enhanced CKD data analysis.
  • To improve the accuracy and efficiency of early CKD detection systems.
  • To leverage natural-inspired algorithms for medical data analysis.

Main Methods:

  • The study employed a snake optimization (SO) algorithm for feature selection in CKD datasets.
  • Five distinct machine learning algorithms were integrated with the SO algorithm.
  • The CKD-SO framework was developed for predicting kidney and liver diseases.

Main Results:

  • The developed CKD-SO model achieved a highly accurate prediction rate of 99.7% for CKD detection.
  • The SO algorithm effectively identified the most relevant features for disease prediction.
  • The study demonstrated the potential of SO in optimizing ML models for medical data.

Conclusions:

  • The CKD-SO framework represents a significant advancement in automated CKD detection.
  • Early and accurate CKD detection using this method can facilitate timely interventions.
  • This approach has the potential to reduce the global burden of CKD-related mortality and morbidity.