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Browse files- app.py +379 -0
- best_model.pkl +3 -0
app.py
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| 1 |
+
import streamlit as st
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| 2 |
+
import pandas as pd
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| 3 |
+
import numpy as np
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| 4 |
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import pickle
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| 5 |
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from PIL import Image
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| 6 |
+
import plotly.express as px
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| 7 |
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import plotly.graph_objects as go
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| 8 |
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from streamlit_lottie import st_lottie
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| 9 |
+
import requests
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| 10 |
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import json
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| 11 |
+
from streamlit_option_menu import option_menu
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| 12 |
+
import time
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| 13 |
+
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| 14 |
+
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| 15 |
+
# Ajoutez ceci au début du code, juste après les imports
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| 16 |
+
@st.cache_resource
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| 17 |
+
def load_model():
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| 18 |
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"""
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| 19 |
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Charge le modèle sauvegardé
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| 20 |
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"""
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try:
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| 22 |
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with open('models/best_model.pkl', 'rb') as f:
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| 23 |
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model = pickle.load(f)
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| 24 |
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return model
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| 25 |
+
except Exception as e:
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| 26 |
+
st.error(f"Erreur lors du chargement du modèle: {str(e)}")
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| 27 |
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return None
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| 28 |
+
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| 29 |
+
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| 30 |
+
# Configuration de la page
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| 31 |
+
st.set_page_config(
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| 32 |
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page_title="HeartGuard AI - Prédiction de Risque Cardiaque",
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| 33 |
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page_icon="❤️",
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| 34 |
+
layout="wide",
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| 35 |
+
initial_sidebar_state="expanded"
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| 36 |
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)
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| 37 |
+
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| 38 |
+
# Style CSS personnalisé
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| 39 |
+
st.markdown("""
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| 40 |
+
<style>
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| 41 |
+
@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@300;400;500;600;700&display=swap');
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| 42 |
+
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| 43 |
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* {
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| 44 |
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font-family: 'Poppins', sans-serif;
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| 45 |
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}
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| 46 |
+
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| 47 |
+
.main {
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| 48 |
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background: linear-gradient(135deg, #f5f7fa 0%, #e4e8eb 100%);
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| 49 |
+
}
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| 50 |
+
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| 51 |
+
.stButton>button {
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| 52 |
+
background: linear-gradient(45deg, #ff4b4b, #ff6b6b);
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| 53 |
+
color: white;
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| 54 |
+
border-radius: 25px;
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| 55 |
+
padding: 10px 25px;
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| 56 |
+
border: none;
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| 57 |
+
box-shadow: 0 4px 15px rgba(255, 75, 75, 0.3);
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| 58 |
+
transition: all 0.3s ease;
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| 59 |
+
}
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| 60 |
+
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| 61 |
+
.stButton>button:hover {
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| 62 |
+
transform: translateY(-2px);
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| 63 |
+
box-shadow: 0 6px 20px rgba(255, 75, 75, 0.4);
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| 64 |
+
}
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| 65 |
+
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| 66 |
+
.sidebar .sidebar-content {
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| 67 |
+
background: linear-gradient(180deg, #ffffff 0%, #f8f9fa 100%);
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| 68 |
+
box-shadow: 2px 0 10px rgba(0,0,0,0.1);
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| 69 |
+
}
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| 70 |
+
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| 71 |
+
.stSelectbox, .stNumberInput {
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| 72 |
+
border-radius: 10px;
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| 73 |
+
}
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| 74 |
+
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| 75 |
+
.css-1d391kg {
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| 76 |
+
padding: 2rem 1rem;
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| 77 |
+
}
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| 78 |
+
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| 79 |
+
.stProgress > div > div {
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| 80 |
+
background-color: #ff4b4b;
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| 81 |
+
}
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| 82 |
+
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| 83 |
+
.stMarkdown {
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| 84 |
+
color: #2c3e50;
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| 85 |
+
}
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| 86 |
+
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| 87 |
+
.stAlert {
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| 88 |
+
border-radius: 10px;
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| 89 |
+
}
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| 90 |
+
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| 91 |
+
.css-1v0mbdj {
|
| 92 |
+
border-radius: 10px;
|
| 93 |
+
}
|
| 94 |
+
</style>
|
| 95 |
+
""", unsafe_allow_html=True)
|
| 96 |
+
|
| 97 |
+
# Fonction pour charger les animations Lottie
|
| 98 |
+
def load_lottieurl(url: str):
|
| 99 |
+
r = requests.get(url)
|
| 100 |
+
if r.status_code != 200:
|
| 101 |
+
return None
|
| 102 |
+
return r.json()
|
| 103 |
+
|
| 104 |
+
# Chargement des animations
|
| 105 |
+
heart_animation = load_lottieurl("https://assets5.lottiefiles.com/packages/lf20_49rdyysj.json")
|
| 106 |
+
loading_animation = load_lottieurl("https://assets3.lottiefiles.com/packages/lf20_p8bfn5to.json")
|
| 107 |
+
|
| 108 |
+
# Sidebar avec menu stylisé
|
| 109 |
+
with st.sidebar:
|
| 110 |
+
st_lottie(heart_animation, height=150, key="sidebar_animation")
|
| 111 |
+
|
| 112 |
+
selected = option_menu(
|
| 113 |
+
menu_title="Navigation",
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| 114 |
+
options=["Accueil", "Prédiction", "À Propos"],
|
| 115 |
+
icons=['house', 'heart-pulse', 'info-circle'],
|
| 116 |
+
menu_icon="cast",
|
| 117 |
+
default_index=0,
|
| 118 |
+
styles={
|
| 119 |
+
"container": {"padding": "0!important", "background-color": "#ffffff"},
|
| 120 |
+
"icon": {"color": "#ff4b4b", "font-size": "20px"},
|
| 121 |
+
"nav-link": {
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| 122 |
+
"font-size": "16px",
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| 123 |
+
"text-align": "left",
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| 124 |
+
"margin": "0px",
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| 125 |
+
"padding": "10px",
|
| 126 |
+
"--hover-color": "#ff4b4b",
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| 127 |
+
},
|
| 128 |
+
"nav-link-selected": {"background-color": "#ff4b4b"},
|
| 129 |
+
}
|
| 130 |
+
)
|
| 131 |
+
|
| 132 |
+
# Contenu principal
|
| 133 |
+
if selected == "Accueil":
|
| 134 |
+
st.title("❤️ HeartGuard AI")
|
| 135 |
+
st.markdown("### Votre Assistant de Santé Cardiaque Intelligent")
|
| 136 |
+
|
| 137 |
+
col1, col2 = st.columns([2, 1])
|
| 138 |
+
with col1:
|
| 139 |
+
st.markdown("""
|
| 140 |
+
Bienvenue dans HeartGuard AI, votre outil de prédiction de risque cardiaque basé sur l'intelligence artificielle.
|
| 141 |
+
|
| 142 |
+
Notre application utilise des algorithmes avancés de machine learning pour évaluer votre risque cardiaque
|
| 143 |
+
en fonction de plusieurs paramètres de santé.
|
| 144 |
+
|
| 145 |
+
### Fonctionnalités principales :
|
| 146 |
+
- 🔍 Analyse précise des facteurs de risque
|
| 147 |
+
- 📊 Visualisations interactives
|
| 148 |
+
- 🎯 Prédictions en temps réel
|
| 149 |
+
- 📱 Interface intuitive et moderne
|
| 150 |
+
""")
|
| 151 |
+
|
| 152 |
+
with col2:
|
| 153 |
+
st_lottie(heart_animation, height=300, key="main_animation")
|
| 154 |
+
|
| 155 |
+
elif selected == "Prédiction":
|
| 156 |
+
st.title("Prédiction de Risque Cardiaque")
|
| 157 |
+
|
| 158 |
+
# Formulaire de prédiction avec animation de chargement
|
| 159 |
+
with st.form("prediction_form"):
|
| 160 |
+
col1, col2 = st.columns(2)
|
| 161 |
+
|
| 162 |
+
with col1:
|
| 163 |
+
st.subheader("Informations Personnelles")
|
| 164 |
+
age = st.number_input("Âge", min_value=0, max_value=120, value=50)
|
| 165 |
+
male = st.selectbox("Genre", ["Femme", "Homme"])
|
| 166 |
+
male = 1 if male == "Homme" else 0
|
| 167 |
+
|
| 168 |
+
st.subheader("Mode de Vie")
|
| 169 |
+
current_smoker = st.selectbox("Fumeur actuel", ["Non", "Oui"])
|
| 170 |
+
current_smoker = 1 if current_smoker == "Oui" else 0
|
| 171 |
+
cigs_per_day = st.number_input("Nombre de cigarettes par jour", min_value=0, max_value=100, value=0)
|
| 172 |
+
|
| 173 |
+
with col2:
|
| 174 |
+
st.subheader("Paramètres de Santé")
|
| 175 |
+
bp_meds = st.selectbox("Médicaments pour la tension", ["Non", "Oui"])
|
| 176 |
+
bp_meds = 1 if bp_meds == "Oui" else 0
|
| 177 |
+
diabetes = st.selectbox("Diabète", ["Non", "Oui"])
|
| 178 |
+
diabetes = 1 if diabetes == "Oui" else 0
|
| 179 |
+
tot_chol = st.number_input("Cholestérol total", min_value=0, max_value=700, value=200)
|
| 180 |
+
sys_bp = st.number_input("Pression artérielle systolique", min_value=0, max_value=300, value=120)
|
| 181 |
+
dia_bp = st.number_input("Pression artérielle diastolique", min_value=0, max_value=200, value=80)
|
| 182 |
+
bmi = st.number_input("IMC", min_value=0.0, max_value=100.0, value=25.0)
|
| 183 |
+
heart_rate = st.number_input("Fréquence cardiaque", min_value=0, max_value=200, value=75)
|
| 184 |
+
glucose = st.number_input("Glucose", min_value=0, max_value=400, value=80)
|
| 185 |
+
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| 186 |
+
submit_button = st.form_submit_button("Analyser le Risque")
|
| 187 |
+
|
| 188 |
+
if submit_button:
|
| 189 |
+
with st.spinner("Analyse en cours..."):
|
| 190 |
+
st_lottie(loading_animation, height=100, key="loading")
|
| 191 |
+
|
| 192 |
+
# Préparation des données
|
| 193 |
+
input_data = pd.DataFrame({
|
| 194 |
+
'male': [male],
|
| 195 |
+
'age': [age],
|
| 196 |
+
'currentSmoker': [current_smoker],
|
| 197 |
+
'cigsPerDay': [cigs_per_day],
|
| 198 |
+
'BPMeds': [bp_meds],
|
| 199 |
+
'diabetes': [diabetes],
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| 200 |
+
'totChol': [tot_chol],
|
| 201 |
+
'sysBP': [sys_bp],
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| 202 |
+
'diaBP': [dia_bp],
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| 203 |
+
'BMI': [bmi],
|
| 204 |
+
'heartRate': [heart_rate],
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| 205 |
+
'glucose': [glucose]
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| 206 |
+
})
|
| 207 |
+
|
| 208 |
+
# Chargement et prédiction
|
| 209 |
+
model = load_model()
|
| 210 |
+
prediction = model.predict(input_data)[0]
|
| 211 |
+
probability = model.predict_proba(input_data)[0]
|
| 212 |
+
|
| 213 |
+
# Affichage des résultats avec animations
|
| 214 |
+
st.markdown("---")
|
| 215 |
+
col1, col2, col3 = st.columns(3)
|
| 216 |
+
|
| 217 |
+
with col1:
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| 218 |
+
st.subheader("Résultat de l'Analyse")
|
| 219 |
+
if prediction == 0:
|
| 220 |
+
st.success("Risque Cardiaque: Faible")
|
| 221 |
+
else:
|
| 222 |
+
st.error("Risque Cardiaque: Élevé")
|
| 223 |
+
|
| 224 |
+
with col2:
|
| 225 |
+
st.subheader("Probabilité de Risque")
|
| 226 |
+
fig = go.Figure(go.Indicator(
|
| 227 |
+
mode="gauge+number+delta",
|
| 228 |
+
value=probability[1]*100,
|
| 229 |
+
domain={'x': [0, 1], 'y': [0, 1]},
|
| 230 |
+
title={'text': "Probabilité (%)"},
|
| 231 |
+
gauge={
|
| 232 |
+
'axis': {'range': [0, 100]},
|
| 233 |
+
'bar': {'color': "darkblue"},
|
| 234 |
+
'steps': [
|
| 235 |
+
{'range': [0, 30], 'color': "lightgreen"},
|
| 236 |
+
{'range': [30, 70], 'color': "yellow"},
|
| 237 |
+
{'range': [70, 100], 'color': "red"}
|
| 238 |
+
],
|
| 239 |
+
'threshold': {
|
| 240 |
+
'line': {'color': "red", 'width': 4},
|
| 241 |
+
'thickness': 0.75,
|
| 242 |
+
'value': 50
|
| 243 |
+
}
|
| 244 |
+
}))
|
| 245 |
+
st.plotly_chart(fig, use_container_width=True)
|
| 246 |
+
|
| 247 |
+
with col3:
|
| 248 |
+
st.subheader("Facteurs de Risque")
|
| 249 |
+
risk_factors = []
|
| 250 |
+
if age > 60: risk_factors.append("Âge avancé")
|
| 251 |
+
if current_smoker: risk_factors.append("Tabagisme")
|
| 252 |
+
if bp_meds: risk_factors.append("Hypertension")
|
| 253 |
+
if diabetes: risk_factors.append("Diabète")
|
| 254 |
+
if bmi > 30: risk_factors.append("Obésité")
|
| 255 |
+
if tot_chol > 240: risk_factors.append("Cholestérol élevé")
|
| 256 |
+
|
| 257 |
+
if risk_factors:
|
| 258 |
+
for factor in risk_factors:
|
| 259 |
+
st.warning(factor)
|
| 260 |
+
else:
|
| 261 |
+
st.info("Aucun facteur de risque majeur identifié")
|
| 262 |
+
|
| 263 |
+
elif selected == "À Propos":
|
| 264 |
+
st.markdown("""
|
| 265 |
+
<style>
|
| 266 |
+
.about-container {
|
| 267 |
+
max-width: 800px;
|
| 268 |
+
margin: 0 auto;
|
| 269 |
+
padding: 20px;
|
| 270 |
+
background: white;
|
| 271 |
+
border-radius: 15px;
|
| 272 |
+
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
|
| 273 |
+
}
|
| 274 |
+
.title {
|
| 275 |
+
color: #2c3e50;
|
| 276 |
+
font-size: 2.5em;
|
| 277 |
+
text-align: center;
|
| 278 |
+
margin-bottom: 30px;
|
| 279 |
+
font-weight: 600;
|
| 280 |
+
}
|
| 281 |
+
.description {
|
| 282 |
+
color: #555;
|
| 283 |
+
font-size: 1.1em;
|
| 284 |
+
line-height: 1.6;
|
| 285 |
+
text-align: center;
|
| 286 |
+
margin-bottom: 40px;
|
| 287 |
+
padding: 0 20px;
|
| 288 |
+
}
|
| 289 |
+
.profile-container {
|
| 290 |
+
display: flex;
|
| 291 |
+
flex-direction: column;
|
| 292 |
+
align-items: center;
|
| 293 |
+
gap: 20px;
|
| 294 |
+
padding: 20px;
|
| 295 |
+
}
|
| 296 |
+
.profile-image {
|
| 297 |
+
width: 200px;
|
| 298 |
+
height: 200px;
|
| 299 |
+
border-radius: 50%;
|
| 300 |
+
border: 4px solid #ff4b4b;
|
| 301 |
+
box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
|
| 302 |
+
object-fit: cover;
|
| 303 |
+
}
|
| 304 |
+
.profile-info {
|
| 305 |
+
text-align: center;
|
| 306 |
+
}
|
| 307 |
+
.profile-info h4 {
|
| 308 |
+
color: #2c3e50;
|
| 309 |
+
font-size: 1.8em;
|
| 310 |
+
margin: 10px 0;
|
| 311 |
+
}
|
| 312 |
+
.contact-info {
|
| 313 |
+
display: flex;
|
| 314 |
+
flex-direction: column;
|
| 315 |
+
gap: 10px;
|
| 316 |
+
align-items: center;
|
| 317 |
+
margin-top: 15px;
|
| 318 |
+
}
|
| 319 |
+
.contact-link {
|
| 320 |
+
display: flex;
|
| 321 |
+
align-items: center;
|
| 322 |
+
gap: 10px;
|
| 323 |
+
color: #555;
|
| 324 |
+
text-decoration: none;
|
| 325 |
+
padding: 8px 15px;
|
| 326 |
+
border-radius: 25px;
|
| 327 |
+
background: #f8f9fa;
|
| 328 |
+
transition: all 0.3s ease;
|
| 329 |
+
}
|
| 330 |
+
.contact-link:hover {
|
| 331 |
+
background: #ff4b4b;
|
| 332 |
+
color: white;
|
| 333 |
+
transform: translateY(-2px);
|
| 334 |
+
}
|
| 335 |
+
</style>
|
| 336 |
+
|
| 337 |
+
<div class="about-container">
|
| 338 |
+
<h1 class="title">Mon Parcours</h1>
|
| 339 |
+
|
| 340 |
+
<p class="description">
|
| 341 |
+
Je suis un passionné de l'intelligence artificielle et de la donnée.
|
| 342 |
+
Actuellement en Master 2 en IA et Big Data, je travaille sur des solutions
|
| 343 |
+
innovantes dans le domaine de l'Intelligence Artificielle appliquée à la santé.
|
| 344 |
+
</p>
|
| 345 |
+
|
| 346 |
+
<div class="profile-container">
|
| 347 |
+
<img src="https://avatars.githubusercontent.com/u/TheBeyonder237"
|
| 348 |
+
alt="Ngoue David"
|
| 349 |
+
class="profile-image">
|
| 350 |
+
|
| 351 |
+
<div class="profile-info">
|
| 352 |
+
<h4>Ngoue David</h4>
|
| 353 |
+
|
| 354 |
+
<div class="contact-info">
|
| 355 |
+
<a href="mailto:ngouedavidrogeryannick@gmail.com" class="contact-link">
|
| 356 |
+
📧 ngouedavidrogeryannick@gmail.com
|
| 357 |
+
</a>
|
| 358 |
+
<a href="https://github.com/TheBeyonder237" target="_blank" class="contact-link">
|
| 359 |
+
🌐 Profil GitHub
|
| 360 |
+
</a>
|
| 361 |
+
<div class="contact-link">
|
| 362 |
+
🎓 Master 2 IA & Big Data
|
| 363 |
+
</div>
|
| 364 |
+
</div>
|
| 365 |
+
</div>
|
| 366 |
+
</div>
|
| 367 |
+
</div>
|
| 368 |
+
""", unsafe_allow_html=True)
|
| 369 |
+
|
| 370 |
+
# Ajout d'une animation Lottie
|
| 371 |
+
st_lottie(heart_animation, height=200, key="about_animation")
|
| 372 |
+
|
| 373 |
+
# Footer
|
| 374 |
+
st.markdown("""
|
| 375 |
+
<div style="text-align: center; margin-top: 30px; color: #666;">
|
| 376 |
+
<p>Développé avec ❤️ par Ngoue David</p>
|
| 377 |
+
<p style="font-size: 0.8em;">© 2024 HeartGuard AI. Tous droits réservés.</p>
|
| 378 |
+
</div>
|
| 379 |
+
""", unsafe_allow_html=True)
|
best_model.pkl
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f1eb3c39a9a250d346ec0818bb84b68eb9790c19e977e35c3da21d031312ba85
|
| 3 |
+
size 7392293
|