app.py

import streamlit as st
import pandas as pd
import pickle
import joblib

st.title("Prediction of Death Event")

# import model
model = pickle.load(open("boosted.pkl", "rb"))



st.write('Insert feature below to predict')

# user input
age = st.number_input(label='Age', min_value=40, max_value=95, value=40, step=1)
anaemia = st.selectbox(label='Anaemia', options=[0,1])
creatinine_phosphokinase = st.number_input(label='Creatinine Phosphokinase', min_value=23.0, max_value=1954.5, value=23.0, step=0.1)
diabetes = st.selectbox(label='Diabetes', options=[0,1])
ejection_fraction = st.number_input(label='Ejection Fraction', min_value=14.0, max_value=73.4, value=14.0, step=0.1)
high_blood_pressure = st.selectbox(label='High Blood Pressure', options=[0,1])
platelets = st.number_input(label='Platelets', min_value=25100, max_value=543000, value=26000, step=10)
serum_creatinine = st.number_input(label='Serum Creatinine', min_value=0.5, max_value=4.2, value=1.5, step=0.1)
smoking	= st.selectbox(label='Smoking', options=[0,1])
time = st.number_input(label='Time', min_value=4, max_value=285, value=10, step=1)

# convert into dataframe
data = pd.DataFrame({'Age': [age],
                'Anaemia': [anaemia],
                'Creatinine Phosphokinas': [creatinine_phosphokinase],
                'Diabetes':[diabetes],
                'Ejection Fraction': [ejection_fraction],
                'High Blood Pressure': [high_blood_pressure],
                'Platelets': [platelets],
                'Serum Creatinine': [serum_creatinine],
                'Smoking': [smoking],
                'Time': [time]})

# model predict

clas = model.predict(data).tolist()[0]

# interpretation
st.write('Classification Result: ')
if clas == 1:
    st.text('Die')
else:
    st.text('Alive')