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APPENDICES

APPENDIX A: FLASK APP.PY CODE

from flask import Flask, render_template, request, redirect,url_for,
session, flash, jsonify
from joblib import load
import mysql.connector
import pandas as pd
import matplotlib
matplotlib.use('Agg')
import json

admin_username = 'admin';
admin_password = "123";

app = Flask(__name__)
app.secret_key = 'anginahmarcare'
app.config['SESSION_TYPE'] = 'filesystem'

def get_db_connection():
return mysql.connector.connect(
host="localhost",
user="root",
password="",
database="anginahmarv2"

)

# Load the trained model and label encoders
model = load('trained_model.joblib')
le_gender = load('le_gender.joblib')
le_smoking_status = load('le_smoking_status.joblib')
le_ever_married = load('le_ever_married.joblib')
le_work_type = load('le_work_type.joblib')
le_Residence_type = load('le_Residence_type.joblib')
le_age_category = load('le_age_category.joblib')
le_bmi_category = load('le_bmi_category.joblib')

# Function to categorize age and BMI
def categorize_age(age):
if age <= 14:
return 'Child'
elif age <= 24:
return 'Youth'
elif age <= 64:
return 'Adult'
else:
return 'Senior'

def categorize_bmi(bmi):
if bmi < 18.5:
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