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| import joblib | |
| import pandas as pd | |
| from extract_features import extract_features | |
| # Load the trained model and feature list | |
| model = joblib.load("final_model.pkl") # Make sure it's your trained model | |
| expected_features = joblib.load("expected_features.pkl") # A list of 29 feature names used during training | |
| # Set your test audio file here | |
| file_path = "patient_1_healthy.wav" # or patient_2_cognitive_decline.wav | |
| # Extract features from the file | |
| features = extract_features(file_path) | |
| # Align features to training feature set | |
| X = pd.DataFrame([features]) | |
| X = X.reindex(columns=expected_features, fill_value=0) | |
| # Predict | |
| prediction = model.predict(X)[0] | |
| prob = model.predict_proba(X).max() | |
| print(f"🧠 Predicted Cognitive Status: {prediction} (Confidence: {prob:.2f})") | |