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sanjay-kv
Is there an existing issue for this?
Feature Description
This work aims to accurately predict Chronic Kidney Disease (CKD) using a robust Artificial Neural Network model. It compares its performance to various machine learning algorithms, ultimately achieving an impressive accuracy of 98%, making it a promising tool for CKD diagnosis.
Use Case
Advancing the accuracy of Chronic Kidney Disease (CKD) prediction is crucial due to its widespread impact and severe consequences. Globally, CKD affects approximately 10% of the population, yet a staggering 90% of cases remain undiagnosed until reaching advanced stages. By improving predictive models, we can detect CKD earlier, potentially reducing complications and improving patient outcomes.
Benefits
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Priority
High
Record