Saurabh641444/Chronic-Kidney-Disease-Prediction
This repository contain code of Chronic Kidney Disease Detection Prediction Project. The goal of this project is predict the chronic kidney disease using parameters like specific gravity, Red Blood count, Hemoglobin, Hyper tension etc.. The machine learning algorithm random forest algorithm is used with hyperparameter tuning which is having 97.5% accuracy.
This tool helps medical professionals quickly assess a patient's risk of chronic kidney disease (CKD). By inputting various patient parameters like blood pressure, specific gravity, hemoglobin levels, and presence of diabetes, it provides a prediction of whether the patient likely has CKD. It's designed for doctors, nurses, or other healthcare providers in a clinical setting to aid in early diagnosis.
No commits in the last 6 months.
Use this if you are a healthcare professional needing a quick predictive assessment of chronic kidney disease based on patient physiological data.
Not ideal if you require a diagnostic tool that provides definitive medical diagnoses or if you need to analyze highly unstructured patient notes.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Nov 22, 2021
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