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Parkinson-Disease-Prediction

The premium Open Source alternative to UPDRS Clinical Assessment

🎯 Best for:Researchers looking for a non-invasive, scalable method for early neurodegenerative screening.
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What is Parkinson-Disease-Prediction?

Replaces subjective clinical observation with a machine learning pipeline that analyzes vocal features to detect Parkinson's disease. It utilizes k-Nearest Neighbors and Neural Networks to achieve 98% diagnostic accuracy on speech datasets.

Tech Stack
PythonPharma & Biotechnology

Why Parkinson-Disease-Prediction?

  • • High Matthews Correlation Coefficient (0.96)
  • • Low computational cost for inference
  • • Uses standardized Oxford dataset

Limitations

  • • Small training sample size (195 instances)
  • • Requires high-quality audio input
  • • Not FDA/CE cleared for clinical use
3/3/2026
Last Update
32
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0
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License
Financial Leak Detected

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Competitor Cost
-$1,440
/ year (est. based on UPDRS Clinical Assessment)
Self-Hosted
$0
/ year
Team Size10 Users
150+
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