app.py

import streamlit as st 
import joblib
import numpy as np
## Heading 
html_temp = """
    <div style="background-color:black;padding:10px">
    <h2 style="color:red;text-align:center;">Cardiovascular Health Prediction App </h2>
    </div>
    """
st.markdown(html_temp, unsafe_allow_html=True)

st.write("Enter the Patient  details:")

# model

health_model=joblib.load("health_model.joblib")

scaler_model=joblib.load('scaler_the data_model.joblib')

# Input variables

col1, col2 = st.columns(2)
with col1:
    
    ## Age
    age=st.slider("Slide the AGE of the Patient:",max_value=80,min_value=20)
    
with col2:
    
    ## gender
    option_gen=["Female "," Male"]
    gen=st.selectbox("Select the Gender",option_gen) 
    gender_value=option_gen.index(gen)
    
col1, col2 = st.columns(2)
with col1:
    ## chestpain
    chestpain=st.slider("Slide the chestpain Value:",min_value=0,max_value=3)
    
with col2:
    ## restingBP
    restingBP=st.slider("Slide the Resting  BP of the Patient:",min_value=90,max_value=200)

col1,col2=st.columns(2)
with col1:
    ## serumcholestrol
    serumcholestrol=st.slider("Slide The Serum cholestrol Of a Ptient :",min_value=0,max_value=600)
    
with col2:
    ## fastingbloodsugar
    fastingbloodsugar= st.radio("Is Patient blood is Fasting:", ["YES", "NO"])
    if fastingbloodsugar=="YES":
        fastingbloodsugar_value=1
    else:
       fastingbloodsugar_value=0
    
col1,col2=st.columns(2)

with col1:
   ## restingrelectro
    restingrelectro=st.slider("Slide The restingrelectro of a Patient :",min_value=0,max_value=2)
        
with col2:
    ## maxheartrate
    maxheartrate=st.slider("Slide The max heart rate  of the Patient :",min_value=70,max_value=200)

col1,col2=st.columns(2)
with col1:
    ## exerciseangia
    exerciseangia=st.slider("Slide the exerciseangia Value:",min_value=0,max_value=1)
    

with col2:
    ##oldpeak'
    oldpeak=st.slider("Silde the oldpeak :",max_value=6.2,min_value=0.0,value=0.1)
    
    
col1,col2=st.columns(2)
with col1:
    ## slope
    slope=st.slider("Silde the slope of the Patient :",max_value=3,min_value=0,value=1)
    
with col2:
    ## noofmajorvessels
    noofmajorvessels=st.slider("Silde the No of Major Vessels to  a Patient :",max_value=3,min_value=0,value=1)


if st.button("Submit"):
    
    # st.write("before scaleing:",[age,gender_value,chestpain,restingBP,serumcholestrol,fastingbloodsugar_value,restingrelectro,
    #                              maxheartrate,exerciseangia,oldpeak,slope,noofmajorvessels])
    # Scaler the values
    scaler_val = scaler_model.transform([[age,gender_value,chestpain,restingBP,serumcholestrol,fastingbloodsugar_value,restingrelectro,
                                 maxheartrate,exerciseangia,oldpeak,slope,noofmajorvessels]])
    
    # st.write("after scaleing:",scaler_val)
    
    output = health_model.predict(scaler_val)

    
    if output ==0:
        st.write("The patient is Healthy")
    else:
        st.write("The Patient has Heart Disease")