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import streamlit as st
import pickle
import pandas as pd
from sklearn.tree import DecisionTreeClassifier
import warnings
warnings.filterwarnings("ignore")
with open('TreeModel.pkl', 'rb') as f:
model = pickle.load(f)
def get_user_input():
age = st.number_input('Age', min_value=1, max_value=100, value=50)
gender = st.radio('Gender', options=['Male', 'Female'])
gender = 1 if gender == 'Male' else 0
impluse = st.number_input('Impluse', min_value=0, max_value=1000, value=50)
pressurehight = st.number_input('Pressure High', min_value=0, max_value=250, value=120)
pressurelow = st.number_input('Pressure Low', min_value=0, max_value=150, value=80)
glucose = st.number_input('Glucose', min_value=0.0, max_value=500.0, value=100.0)
kcm = st.number_input('KCM', min_value=0.0, max_value=300.0, value=10.0)
troponin = st.number_input('Troponin', min_value=0.0, max_value=10.0, value=0.1)
# Return the user input as a DataFrame
user_input = pd.DataFrame([[age, gender, impluse, pressurehight, pressurelow, glucose, kcm, troponin]],
columns=['age', 'gender', 'impluse', 'pressurehight', 'pressurelow', 'glucose', 'kcm', 'troponin'])
return user_input
# Main function
def main():
st.title("Heart Disease Predict App❤️🩺")
st.markdown("""
This is a simple web app to predict the likelihood of heart disease (positive or negative) based on inputs.
""")
# Input form section
with st.expander('Enter your data'):
user_input = get_user_input()
# Submit button for making prediction
if st.button('Submit'):
# Display the user's input for confirmation
st.subheader('User Input:')
st.write(user_input)
# Make predictions using the loaded model
prediction = model.predict(user_input)
# Display prediction result
if prediction[0] == 1:
st.success("Prediction: Positive (Heart Disease Likely)")
else:
st.markdown("<h3 style='color:red;'>Prediction: Negative (Heart Disease Unlikely)</h3>", unsafe_allow_html=True)
if __name__ == '__main__':
main()
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