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Is It Time for Machine Learning Algorithms to Predict the Risk of Kidney Failure in Patients with Chronic Kidney
Charat Thongprayoon1, Wisit Kaewput2, Avishek Choudhury3
1Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN 55905, USA.
Journal of Clinical Medicine
|April 3, 2021
Abstract:
Chronic kidney disease (CKD) is a common clinical problem affecting more than 800 million people with different kidney diseases [...].
Insights
Chronic kidney disease (CKD) affects over 800 million people globally. Research aims to understand the diverse range of kidney diseases impacting global health.
Area of Science:
- Nephrology
- Public Health
Background:
- Chronic kidney disease (CKD) represents a significant global health challenge, impacting over 800 million individuals worldwide.
- The condition encompasses a wide spectrum of kidney pathologies, underscoring the need for comprehensive understanding and management strategies.
Discussion:
- CKD's prevalence highlights the urgent need for advanced diagnostic tools and therapeutic interventions.
- Exploring the diverse etiologies of kidney diseases is crucial for developing targeted treatment approaches.
Key Insights:
- The sheer scale of CKD necessitates a multi-faceted approach involving healthcare providers, researchers, and policymakers.
- Understanding the varied presentations of kidney diseases is fundamental to improving patient outcomes.
Outlook:
- Future research should focus on early detection biomarkers and innovative therapies for different kidney diseases.
- Collaborative efforts are essential to mitigate the growing burden of CKD on global health systems.
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