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early dementia detection just through voice
Our team has developed two machine learning-based regression models to screen for mild cognitive impairment, trained on eight voice biomarkers. These models have shown over 80% accuracy in initial testing, and we are continuing to collect data to refine and improve their precision.
Techniques: XGBoost, KNN, Random Forest, VotingClassifier, Standard Scalar, Gaussian Weights, CrossValidation
Techniques: LSTM, Sigmoid, GeLU, Dense, Dropout,Adam, SelectKBest, Gradient Clipping, Standard Scalar, EarlyStopping
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Analysis Proces Model 1: Regression
Techniques: XGBoost, KNN, Random Forest, VotingClassifier, Standard Scalar, Gaussian Weights, CrossValidation Model 2: Neural Network
Techniques: LSTM, Sigmoid, GeLU, Dense, Dropout,Adam, SelectKBest, Gradient Clipping, Standard Scalar, EarlyStopping