rohanmistry231/Parkinsons-Disease-Classification
A Python-based machine learning project for classifying Parkinson's disease using patient data and algorithms like XGBoost and Random Forest. Includes data preprocessing, feature analysis, and model evaluation with Scikit-learn and Pandas for accurate predictions.
This project helps medical practitioners and researchers screen for Parkinson's Disease. It takes biomedical voice measurements from patients as input and predicts whether an individual is healthy or has Parkinson's Disease. The primary users would be neurologists, clinical researchers, or medical diagnosticians.
No commits in the last 6 months.
Use this if you need a rapid, data-driven method to assess the likelihood of Parkinson's Disease from voice measurements.
Not ideal if you require a diagnostic tool for confirmed medical diagnosis rather than a screening or research aid.
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Language
Python
License
MIT
Category
Last pushed
May 24, 2025
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