Academic Research

Explainable AI for early-stage Parkinson's disease detection through gait sensor data.

ML Researcher Academic 2022

ML investigation with explainability focus for healthcare decision support.

Stack

XGBoostRandom ForestVAESHAPExplainable AI

Context

Machine learning investigation detecting early-stage Parkinson's disease through gait analysis data, with strong emphasis on model interpretability for clinical trust.

Highlights

  • XGBoost + Random Forest + Neural Network comparison
  • Variational Autoencoder for data augmentation
  • SHAP explainability for clinical interpretability

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