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import streamlit as st
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import pickle
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import numpy as np
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model = pickle.load(open("heart_disease_model.pkl", "rb"))
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st.title("Heart Disease Prediction App")
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age = st.number_input("Enter Age", min_value=0, max_value=120)
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sex = st.selectbox("Select Gender", options=["Male", "Female"])
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chest_pain = st.selectbox("Chest Pain Type", options=[1, 2, 3, 4])
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blood_pressure = st.number_input("Enter Blood Pressure", min_value=0)
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cholesterol = st.number_input("Enter Cholesterol Level", min_value=0)
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blood_sugar = st.selectbox("Blood Sugar > 120 mg/dl?", options=[0, 1])
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electrocardiographic_result = st.selectbox("Electrocardiographic Result", options=[0, 1, 2])
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max_heart_rate = st.number_input("Enter Maximum Heart Rate", min_value=0)
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exercise_angina = st.selectbox("Exercise Induced Angina", options=[0, 1])
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oldpeak = st.number_input("Enter Oldpeak", min_value=0.0, max_value=6.0)
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slope = st.selectbox("Slope of the Peak Exercise ST Segment", options=[1, 2, 3])
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ca = st.selectbox("Number of Major Vessels Colored by Fluoroscopy", options=[0, 1, 2, 3])
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thalassemia = st.selectbox("Thalassemia", options=[3, 6, 7])
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if st.button("Predict"):
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input_data = [
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age,
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1 if sex == "Male" else 0,
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chest_pain,
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blood_pressure,
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cholesterol,
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blood_sugar,
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electrocardiographic_result,
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max_heart_rate,
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exercise_angina,
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oldpeak,
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slope,
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ca,
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thalassemia
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]
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input_data_reshape = np.asarray(input_data).reshape(1, -1)
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prediction = model.predict(input_data_reshape)
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prediction_text = "Heart Disease Detected" if prediction[0] == 1 else "No Heart Disease Detected"
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st.write(f"Prediction: {prediction_text}")
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