Parkinson-Disease-Detection and Parkinsons-Disease-Classification
About Parkinson-Disease-Detection
guptaharshnavin/Parkinson-Disease-Detection
Parkinson Disease Detection using Machine Learning
This project helps medical researchers and healthcare professionals screen individuals for Parkinson's Disease. It takes voice measurements and other clinical data as input and provides a prediction of whether a person might have Parkinson's. This tool is useful for researchers exploring diagnostic methods and healthcare providers looking for supplementary screening insights.
About Parkinsons-Disease-Classification
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.
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