app.py

import numpy as np
import pandas as pd
import joblib   # for loading the saved model
from sklearn.tree import DecisionTreeClassifier                  #using sklearn decisiontreeclassifier

#from concrete.ml.sklearn.xgb import DecisionTreeClassifier

# Load the saved model
dt = joblib.load('heart_disease_dt_model.pkl')

#fhe_circuit = 
# Make prediction on the first row of data
#prediction = dt.predict(sample_data, fhe="execute")
prediction = dt.predict(sample_data) # clair

# Display the prediction result
print(prediction)
if prediction == 1:
    print("Prediction: The patient is likely to have heart disease.")
else:
    print("Prediction: The patient is unlikely to have heart disease.")