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import gradio as gr
import os
import re
import logging
import tempfile
import shutil
import base64
from datetime import datetime
from PIL import Image
import html # Import the html module for escaping
from .patient_history import PatientHistoryManager, ReportGenerator
def pil_to_base64(pil_image):
"""Convert PIL Image to base64 data URL"""
import io
import base64
from PIL import Image
if pil_image is None:
return None
try:
# Convert image to RGB if it's not already
if pil_image.mode != 'RGB':
pil_image = pil_image.convert('RGB')
buffer = io.BytesIO()
pil_image.save(buffer, format='PNG')
img_str = base64.b64encode(buffer.getvalue()).decode()
return f"data:image/png;base64,{img_str}"
except Exception as e:
logging.error(f"Error converting PIL image to base64: {e}")
return None
class UIComponents:
def __init__(self, auth_manager, database_manager, wound_analyzer):
self.auth_manager = auth_manager
self.database_manager = database_manager
self.wound_analyzer = wound_analyzer
self.current_user = {}
self.patient_history_manager = PatientHistoryManager(database_manager)
self.report_generator = ReportGenerator()
# Ensure uploads directory exists
if not os.path.exists("uploads"):
os.makedirs("uploads", exist_ok=True)
def image_to_base64(self, image_path):
"""Convert image to base64 data URL for embedding in HTML"""
if not image_path or not os.path.exists(image_path):
return None
try:
with open(image_path, "rb") as image_file:
encoded_string = base64.b64encode(image_file.read()).decode()
# Determine image format
image_ext = os.path.splitext(image_path)[1].lower()
if image_ext in [".jpg", ".jpeg"]:
mime_type = "image/jpeg"
elif image_ext == ".png":
mime_type = "image/png"
elif image_ext == ".gif":
mime_type = "image/gif"
else:
mime_type = "image/png" # Default to PNG
return f"data:{mime_type};base64,{encoded_string}"
except Exception as e:
logging.error(f"Error converting image to base64: {e}")
return None
def markdown_to_html(self, markdown_text):
"""Convert markdown text to proper HTML format with enhanced support"""
if not markdown_text:
return ""
# Escape HTML entities first to prevent issues with special characters
html_text = html.escape(markdown_text)
# Convert headers
html_text = re.sub(r"^### (.*?)$", r"<h3>\1</h3>", html_text, flags=re.MULTILINE)
html_text = re.sub(r"^## (.*?)$", r"<h2>\1</h2>", html_text, flags=re.MULTILINE)
html_text = re.sub(r"^# (.*?)$", r"<h1>\1</h1>", html_text, flags=re.MULTILINE)
# Convert bold text
html_text = re.sub(r"\*\*(.*?)\*\*", r"<strong>\1</strong>", html_text)
# Convert italic text
html_text = re.sub(r"\*(.*?)\*", r"<em>\1</em>", html_text)
# Convert code blocks (triple backticks)
html_text = re.sub(r"```(.*?)```", r"<pre><code>\1</code></pre>", html_text, flags=re.DOTALL)
# Convert inline code (single backticks)
html_text = re.sub(r"`(.*?)`", r"<code>\1</code>", html_text)
# Convert blockquotes
html_text = re.sub(r"^> (.*?)$", r"<blockquote>\1</blockquote>", html_text, flags=re.MULTILINE)
# Convert links
html_text = re.sub(r"\[(.*?)\]\((.*?)\)", r"<a href=\"\2\">\1</a>", html_text)
# Convert horizontal rules
html_text = re.sub(r"^\s*[-*_]{3,}\s*$", r"<hr>", html_text, flags=re.MULTILINE)
# Convert bullet points and handle nested lists (simplified for example)
lines = html_text.split("\n")
in_list = False
result_lines = []
for line in lines:
stripped = line.strip()
if stripped.startswith("- "):
if not in_list:
result_lines.append("<ul>")
in_list = True
result_lines.append(f"<li>{stripped[2:]}</li>")
else:
if in_list:
result_lines.append("</ul>")
in_list = False
if stripped:
result_lines.append(f"<p>{stripped}</p>")
else:
result_lines.append("<br>")
if in_list:
result_lines.append("</ul>")
return "\n".join(result_lines)
def get_organizations_dropdown(self):
"""Get list of organizations for dropdown"""
try:
organizations = self.database_manager.get_organizations()
return [f"{org['org_name']} - {org['location']}" for org in organizations]
except Exception as e:
logging.error(f"Error getting organizations: {e}")
return ["Default Hospital - Location"]
def get_custom_css(self):
return """
/* =================== ORIGINAL SMARTHEAL CSS =================== */
/* Global Styling */
body, html {
margin: 0 !important;
padding: 0 !important;
font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', 'Roboto', 'Oxygen', 'Ubuntu', 'Cantarell', sans-serif !important;
background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%) !important;
color: #1A202C !important;
line-height: 1.6 !important;
}
/* Professional Header with Logo */
.medical-header {
background: linear-gradient(135deg, #3182ce 0%, #2c5aa0 100%) !important;
color: white !important;
padding: 32px 40px !important;
border-radius: 20px 20px 0 0 !important;
display: flex !important;
align-items: center !important;
justify-content: center !important;
margin-bottom: 0 !important;
box-shadow: 0 10px 40px rgba(49, 130, 206, 0.3) !important;
border: none !important;
position: relative !important;
overflow: hidden !important;
}
.medical-header::before {
content: '' !important;
position: absolute !important;
top: 0 !important;
left: 0 !important;
right: 0 !important;
bottom: 0 !important;
background: url('data:image/svg+xml,<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 100 100"><defs><pattern id="grid" width="10" height="10" patternUnits="userSpaceOnUse"><path d="M 10 0 L 0 0 0 10" fill="none" stroke="rgba(255,255,255,0.1)" stroke-width="0.5"/></pattern></defs><rect width="100" height="100" fill="url(%23grid)" /></svg>') !important;
opacity: 0.1 !important;
z-index: 1 !important;
}
.medical-header > * {
position: relative !important;
z-index: 2 !important;
}
.logo {
width: 80px !important;
height: 80px !important;
border-radius: 50% !important;
margin-right: 24px !important;
border: 4px solid rgba(255, 255, 255, 0.3) !important;
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2) !important;
background: white !important;
padding: 4px !important;
}
.medical-header h1 {
font-size: 3.5rem !important;
font-weight: 800 !important;
margin: 0 !important;
text-shadow: 2px 2px 8px rgba(0, 0, 0, 0.3) !important;
background: linear-gradient(45deg, #ffffff, #f8f9fa) !important;
-webkit-background-clip: text !important;
-webkit-text-fill-color: transparent !important;
background-clip: text !important;
filter: drop-shadow(2px 2px 4px rgba(0, 0, 0, 0.3)) !important;
}
.medical-header p {
font-size: 1.3rem !important;
margin: 8px 0 0 0 !important;
opacity: 0.95 !important;
font-weight: 500 !important;
text-shadow: 1px 1px 4px rgba(0, 0, 0, 0.2) !important;
}
/* Enhanced Form Styling */
.gr-form {
background: linear-gradient(145deg, #ffffff 0%, #f8f9fa 100%) !important;
border-radius: 20px !important;
padding: 32px !important;
margin: 24px 0 !important;
box-shadow: 0 16px 48px rgba(0, 0, 0, 0.1) !important;
border: 1px solid rgba(229, 62, 62, 0.1) !important;
backdrop-filter: blur(10px) !important;
position: relative !important;
overflow: hidden !important;
}
.gr-form::before {
content: '' !important;
position: absolute !important;
top: 0 !important;
left: 0 !important;
right: 0 !important;
height: 4px !important;
background: linear-gradient(90deg, #e53e3e 0%, #f56565 50%, #e53e3e 100%) !important;
z-index: 1 !important;
}
/* Professional Input Fields */
.gr-textbox, .gr-number {
border-radius: 12px !important;
border: 2px solid #E2E8F0 !important;
background: #FFFFFF !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.05) !important;
font-size: 1rem !important;
color: #1A202C !important;
padding: 16px 20px !important;
}
.gr-textbox:focus,
.gr-number:focus,
.gr-textbox input:focus,
.gr-number input:focus {
border-color: #E53E3E !important;
box-shadow: 0 0 0 4px rgba(229, 62, 62, 0.1) !important;
background: #FFFFFF !important;
outline: none !important;
transform: translateY(-1px) !important;
}
.gr-textbox input,
.gr-number input {
background: transparent !important;
border: none !important;
outline: none !important;
color: #1A202C !important;
font-size: 1rem !important;
width: 100% !important;
padding: 0 !important;
}
.gr-textbox label,
.gr-number label,
.gr-dropdown label,
.gr-radio label,
.gr-checkbox label {
font-weight: 600 !important;
color: #2D3748 !important;
font-size: 1rem !important;
margin-bottom: 8px !important;
display: block !important;
}
/* Enhanced Button Styling */
button.gr-button,
button.gr-button-primary {
background: linear-gradient(135deg, #E53E3E 0%, #C53030 100%) !important;
color: #FFFFFF !important;
border: none !important;
border-radius: 12px !important;
font-weight: 700 !important;
padding: 16px 32px !important;
font-size: 1.1rem !important;
letter-spacing: 0.5px !important;
text-align: center !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
box-shadow: 0 4px 16px rgba(229, 62, 62, 0.3) !important;
position: relative !important;
overflow: hidden !important;
text-transform: uppercase !important;
cursor: pointer !important;
}
button.gr-button::before {
content: '' !important;
position: absolute !important;
top: 0 !important;
left: -100% !important;
width: 100% !important;
height: 100% !important;
background: linear-gradient(90deg, transparent, rgba(255,255,255,0.4), transparent) !important;
transition: left 0.5s !important;
}
button.gr-button:hover::before {
left: 100% !important;
}
button.gr-button:hover,
button.gr-button-primary:hover {
background: linear-gradient(135deg, #C53030 0%, #9C2A2A 100%) !important;
box-shadow: 0 8px 32px rgba(229, 62, 62, 0.4) !important;
transform: translateY(-3px) !important;
}
button.gr-button:active,
button.gr-button-primary:active {
transform: translateY(-1px) !important;
box-shadow: 0 4px 16px rgba(229, 62, 62, 0.5) !important;
}
button.gr-button:disabled {
background: #A0AEC0 !important;
color: #718096 !important;
cursor: not-allowed !important;
box-shadow: none !important;
transform: none !important;
}
/* Professional Status Messages */
.status-success {
background: linear-gradient(135deg, #F0FFF4 0%, #E6FFFA 100%) !important;
border: 2px solid #38A169 !important;
color: #22543D !important;
padding: 20px 24px !important;
border-radius: 16px !important;
font-weight: 600 !important;
margin: 16px 0 !important;
box-shadow: 0 8px 24px rgba(56, 161, 105, 0.2) !important;
backdrop-filter: blur(10px) !important;
}
.status-error {
background: linear-gradient(135deg, #FFF5F5 0%, #FED7D7 100%) !important;
border: 2px solid #E53E3E !important;
color: #742A2A !important;
padding: 20px 24px !important;
border-radius: 16px !important;
font-weight: 600 !important;
margin: 16px 0 !important;
box-shadow: 0 8px 24px rgba(229, 62, 62, 0.2) !important;
backdrop-filter: blur(10px) !important;
}
.status-warning {
background: linear-gradient(135deg, #FFFAF0 0%, #FEEBC8 100%) !important;
border: 2px solid #DD6B20 !important;
color: #9C4221 !important;
padding: 20px 24px !important;
border-radius: 16px !important;
font-weight: 600 !important;
margin: 16px 0 !important;
box-shadow: 0 8px 24px rgba(221, 107, 32, 0.2) !important;
backdrop-filter: blur(10px) !important;
}
/* Professional Card Layout */
.medical-card {
background: linear-gradient(145deg, #FFFFFF 0%, #F7FAFC 100%) !important;
border-radius: 20px !important;
padding: 32px !important;
margin: 24px 0 !important;
box-shadow: 0 16px 48px rgba(0, 0, 0, 0.08) !important;
border: 1px solid rgba(229, 62, 62, 0.1) !important;
backdrop-filter: blur(10px) !important;
position: relative !important;
overflow: hidden !important;
}
.medical-card::before {
content: '' !important;
position: absolute !important;
top: 0 !important;
left: 0 !important;
right: 0 !important;
height: 4px !important;
background: linear-gradient(90deg, #E53E3E 0%, #F56565 50%, #E53E3E 100%) !important;
}
.medical-card-title {
font-size: 1.75rem !important;
font-weight: 700 !important;
color: #1A202C !important;
margin-bottom: 24px !important;
padding-bottom: 16px !important;
border-bottom: 2px solid #E53E3E !important;
text-align: center !important;
position: relative !important;
}
.medical-card-title::after {
content: '' !important;
position: absolute !important;
bottom: -2px !important;
left: 50% !important;
transform: translateX(-50%) !important;
width: 60px !important;
height: 4px !important;
background: linear-gradient(90deg, transparent, #E53E3E, transparent) !important;
border-radius: 2px !important;
}
/* Professional Dropdown Styling */
.gr-dropdown {
border-radius: 12px !important;
border: 2px solid #E2E8F0 !important;
background: #FFFFFF !important;
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1) !important;
box-shadow: 0 2px 8px rgba(0, 0, 0, 0.05) !important;
}
.gr-dropdown:focus,
.gr-dropdown select:focus {
border-color: #E53E3E !important;
box-shadow: 0 0 0 4px rgba(229, 62, 62, 0.1) !important;
outline: none !important;
}
.gr-dropdown select {
background: transparent !important;
border: none !important;
color: #1A202C !important;
font-size: 1rem !important;
padding: 16px 20px !important;
border-radius: 12px !important;
}
/* Radio button styling */
.gr-radio input[type="radio"] {
margin-right: 8px !important;
transform: scale(1.2) !important;
}
.gr-radio label {
display: flex !important;
align-items: center !important;
padding: 8px 0 !important;
font-size: 1rem !important;
line-height: 1.5 !important;
cursor: pointer !important;
color: #1A202C !important;
}
/* Tab styling */
.gr-tab {
color: #1A202C !important;
font-weight: 500 !important;
font-size: 1rem !important;
padding: 12px 20px !important;
background-color: #F7FAFC !important;
}
.gr-tab.selected {
color: #E53E3E !important;
font-weight: 600 !important;
border-bottom: 2px solid #E53E3E !important;
background-color: #FFFFFF !important;
}
/* Image upload styling */
.gr-image {
border: 3px dashed #CBD5E0 !important;
border-radius: 16px !important;
background-color: #F7FAFC !important;
transition: all 0.2s ease !important;
}
.gr-image:hover {
border-color: #E53E3E !important;
background-color: #FFF5F5 !important;
}
/* Analyze button special styling */
#analyze-btn {
background: linear-gradient(135deg, #1B5CF3 0%, #1E3A8A 100%) !important;
color: #FFFFFF !important;
border: none !important;
border-radius: 8px !important;
font-weight: 700 !important;
padding: 14px 28px !important;
font-size: 1.1rem !important;
letter-spacing: 0.5px !important;
text-align: center !important;
transition: all 0.2s ease-in-out !important;
}
#analyze-btn:hover {
background: linear-gradient(135deg, #174ea6 0%, #123b82 100%) !important;
box-shadow: 0 4px 14px rgba(27, 95, 193, 0.4) !important;
transform: translateY(-2px) !important;
}
#analyze-btn:disabled {
background: #A0AEC0 !important;
color: #1A202C !important;
cursor: not-allowed !important;
box-shadow: none !important;
transform: none !important;
}
/* Image gallery styling for better visualization */
.image-gallery {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
gap: 20px;
margin: 20px 0;
}
.image-item {
background: #f8f9fa;
border-radius: 12px;
padding: 15px;
box-shadow: 0 4px 12px rgba(0,0,0,0.1);
text-align: center;
}
.image-item img {
max-width: 100%;
height: auto;
border-radius: 8px;
box-shadow: 0 2px 8px rgba(0,0,0,0.15);
}
.image-item h4 {
margin: 15px 0 5px 0;
color: #2d3748;
font-weight: 600;
}
.image-item p {
margin: 0;
color: #666;
font-size: 0.9em;
}
/* Responsive design */
@media (max-width: 768px) {
.medical-header {
padding: 16px !important;
text-align: center !important;
}
.medical-header h1 {
font-size: 2rem !important;
}
.logo {
width: 48px !important;
height: 48px !important;
margin-right: 16px !important;
}
.gr-form {
padding: 16px !important;
margin: 8px 0 !important;
}
button.gr-button,
button.gr-button-primary {
padding: 14px 20px !important;
font-size: 14px !important;
}
.image-gallery {
grid-template-columns: 1fr;
}
}
"""
def create_interface(self):
"""Create the main Gradio interface with original styling and base64 image embedding"""
with gr.Blocks(css=self.get_custom_css(), title="SmartHeal - AI Wound Care Assistant") as app:
# Header with SmartHeal logo (from original)
logo_url = "https://scontent.fccu31-2.fna.fbcdn.net/v/t39.30808-6/275933824_102121829111657_3325198727201325354_n.jpg?_nc_cat=104&ccb=1-7&_nc_sid=6ee11a&_nc_ohc=45krrEUpcSUQ7kNvwGVdiMW&_nc_oc=AdkTdxEC_TkYGiyDkEtTJZ_DFZELW17XKFmWpswmFqGB7JSdvTyWtnrQyLS0USngEiY&_nc_zt=23&_nc_ht=scontent.fccu31-2.fna&_nc_gid=ufAA4Hj5gTRwON5POYzz0Q&oh=00_AfW1-jLEN5RGeggqOvGgEaK_gdg0EDgxf_VhKbZwFLUO0Q&oe=6897A98B"
gr.HTML(f"""
<div class="medical-header">
<img src="{logo_url}" class="logo" alt="SmartHeal Logo">
<div>
<h1>SmartHeal AI</h1>
<p>Advanced Wound Care Analysis & Clinical Support System</p>
</div>
</div>
""")
# Professional disclaimer (from original)
gr.HTML("""
<div style="border: 2px solid #FF6B6B; background-color: #FFE5E5; padding: 15px; border-radius: 12px; margin: 10px 0;">
<h3 style="color: #D63031; margin-top: 0;">⚠️ IMPORTANT DISCLAIMER</h3>
<p><strong>This model is for testing and educational purposes only and is NOT a replacement for professional medical advice.</strong></p>
<p>Information generated may be inaccurate. Always consult a qualified healthcare provider for medical concerns. This AI system uses chain-of-thought reasoning to show its decision-making process, but should never be used as the sole basis for clinical decisions.</p>
<p><em>Uploaded images may be stored and used for testing and model improvement purposes.</em></p>
</div>
""")
# Main interface with conditional visibility (ORIGINAL STRUCTURE)
with gr.Row():
# Professional Authentication Panel (visible when not logged in)
with gr.Column(visible=True) as auth_panel:
gr.HTML("""
<div style="text-align: center; margin: 40px 0;">
<div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); padding: 40px; border-radius: 20px; box-shadow: 0 20px 40px rgba(0,0,0,0.1); max-width: 500px; margin: 0 auto;">
<h2 style="color: white; font-size: 2.5rem; margin-bottom: 10px; font-weight: 700;">🏥 SmartHeal Access</h2>
<p style="color: rgba(255,255,255,0.9); font-size: 1.1rem; margin-bottom: 30px;">Secure Healthcare Professional Portal</p>
</div>
</div>
""")
with gr.Tabs():
with gr.Tab("🔐 Professional Login") as login_tab:
gr.HTML("""
<div style="background: white; padding: 40px; border-radius: 16px; box-shadow: 0 8px 32px rgba(0,0,0,0.1); margin: 20px auto; max-width: 450px;">
<div style="text-align: center; margin-bottom: 30px;">
<h3 style="color: #2d3748; font-size: 1.8rem; margin-bottom: 8px;">Welcome Back</h3>
<p style="color: #718096; font-size: 1rem;">Access your professional dashboard</p>
</div>
</div>
""")
login_username = gr.Textbox(
label="👤 Username",
placeholder="Enter your username"
)
login_password = gr.Textbox(
label="🔒 Password",
type="password",
placeholder="Enter your secure password"
)
login_btn = gr.Button(
"🚀 Sign In to Dashboard",
variant="primary",
size="lg"
)
login_status = gr.HTML(
value="<div style='text-align: center; color: #718096; font-size: 0.9rem; margin-top: 15px;'>Enter your credentials to access the system</div>"
)
with gr.Tab("📝 New Registration") as signup_tab:
gr.HTML("""
<div style="background: white; padding: 40px; border-radius: 16px; box-shadow: 0 8px 32px rgba(0,0,0,0.1); margin: 20px auto; max-width: 450px;">
<div style="text-align: center; margin-bottom: 30px;">
<h3 style="color: #2d3748; font-size: 1.8rem; margin-bottom: 8px;">Create Account</h3>
<p style="color: #718096; font-size: 1rem;">Join the SmartHeal healthcare network</p>
</div>
</div>
""")
signup_username = gr.Textbox(
label="👤 Username",
placeholder="Choose a unique username"
)
signup_email = gr.Textbox(
label="📧 Email Address",
placeholder="Enter your professional email"
)
signup_password = gr.Textbox(
label="🔒 Password",
type="password",
placeholder="Create a strong password"
)
signup_name = gr.Textbox(
label="👨⚕️ Full Name",
placeholder="Enter your full professional name"
)
signup_role = gr.Radio(
["practitioner", "organization"],
label="🏥 Account Type",
value="practitioner"
)
# Organization-specific fields
with gr.Group(visible=False) as org_fields:
gr.HTML("<h4 style='color: #2d3748; margin: 20px 0 10px 0;'>🏢 Organization Details</h4>")
org_name = gr.Textbox(label="Organization Name", placeholder="Enter organization name")
phone = gr.Textbox(label="Phone Number", placeholder="Enter contact number")
country_code = gr.Textbox(label="Country Code", placeholder="e.g., +1, +44")
department = gr.Textbox(label="Department", placeholder="e.g., Emergency, Surgery")
location = gr.Textbox(label="Location", placeholder="City, State/Province, Country")
# Practitioner-specific fields
with gr.Group(visible=True) as prac_fields:
gr.HTML("<h4 style='color: #2d3748; margin: 20px 0 10px 0;'>🏥 Affiliation</h4>")
organization_dropdown = gr.Dropdown(
choices=self.get_organizations_dropdown(),
label="Select Your Organization"
)
signup_btn = gr.Button(
"✨ Create Professional Account",
variant="primary",
size="lg"
)
signup_status = gr.HTML(
value="<div style='text-align: center; color: #718096; font-size: 0.9rem; margin-top: 15px;'>Fill in your details to create an account</div>"
)
# Practitioner Interface (hidden initially)
with gr.Column(visible=False) as practitioner_panel:
gr.HTML('<div class="medical-card-title">👩⚕️ Practitioner Dashboard</div>')
user_info = gr.HTML("")
logout_btn_prac = gr.Button("🚪 Logout", variant="secondary", elem_classes=["logout-btn"])
# Main tabs for different functions
with gr.Tabs():
# WOUND ANALYSIS TAB
with gr.Tab("🔬 Wound Analysis"):
with gr.Row():
with gr.Column(scale=1):
gr.HTML("<h3>📋 Patient Information</h3>")
patient_name = gr.Textbox(label="Patient Name", placeholder="Enter patient's full name")
patient_age = gr.Number(label="Age", value=30, minimum=0, maximum=120)
patient_gender = gr.Dropdown(
choices=["Male", "Female", "Other"],
label="Gender",
value="Male"
)
gr.HTML("<h3>🩹 Wound Information</h3>")
wound_location = gr.Textbox(label="Wound Location", placeholder="e.g., Left ankle, Right arm")
wound_duration = gr.Textbox(label="Wound Duration", placeholder="e.g., 2 weeks, 1 month")
pain_level = gr.Slider(
minimum=0, maximum=10, value=5, step=1,
label="Pain Level (0-10)"
)
gr.HTML("<h3>⚕️ Clinical Assessment</h3>")
moisture_level = gr.Dropdown(
choices=["Dry", "Moist", "Wet", "Saturated"],
label="Moisture Level",
value="Moist"
)
infection_signs = gr.Dropdown(
choices=["None", "Mild", "Moderate", "Severe"],
label="Signs of Infection",
value="None"
)
diabetic_status = gr.Dropdown(
choices=["Non-diabetic", "Type 1", "Type 2", "Gestational"],
label="Diabetic Status",
value="Non-diabetic"
)
with gr.Column(scale=1):
gr.HTML("<h3>📸 Wound Image Upload</h3>")
wound_image = gr.Image(
label="Upload Wound Image",
type="filepath",
elem_classes=["image-upload"]
)
gr.HTML("<h3>📝 Medical History</h3>")
previous_treatment = gr.Textbox(
label="Previous Treatment",
placeholder="Describe any previous treatments...",
lines=3
)
medical_history = gr.Textbox(
label="Medical History",
placeholder="Relevant medical conditions, surgeries, etc...",
lines=3
)
medications = gr.Textbox(
label="Current Medications",
placeholder="List current medications...",
lines=2
)
allergies = gr.Textbox(
label="Known Allergies",
placeholder="List any known allergies...",
lines=2
)
additional_notes = gr.Textbox(
label="Additional Notes",
placeholder="Any additional clinical observations...",
lines=3
)
analyze_btn = gr.Button("🔬 Analyze Wound", variant="primary", size="lg", elem_id="analyze-btn")
analysis_output = gr.HTML("")
# PATIENT HISTORY TAB
with gr.Tab("📋 Patient History"):
with gr.Row():
with gr.Column(scale=2):
gr.HTML("<h3>📊 Patient History Dashboard</h3>")
history_btn = gr.Button("📋 Load Patient History", variant="primary")
patient_history_output = gr.HTML("")
with gr.Column(scale=1):
gr.HTML("<h3>🔍 Search Specific Patient</h3>")
search_patient_name = gr.Textbox(
label="Patient Name",
placeholder="Enter patient name to search..."
)
search_patient_btn = gr.Button("🔍 Search Patient History", variant="secondary")
specific_patient_output = gr.HTML("")
# Event handlers
def handle_login(username, password):
user_data = self.auth_manager.authenticate_user(username, password)
if user_data:
self.current_user = user_data
return {
auth_panel: gr.update(visible=False),
practitioner_panel: gr.update(visible=True),
login_status: "<div class='status-success'>✅ Login successful! Welcome to SmartHeal</div>"
}
else:
return {
login_status: "<div class='status-error'>❌ Invalid credentials. Please try again.</div>"
}
def handle_signup(username, email, password, name, role, org_name, phone, country_code, department, location, organization_dropdown):
try:
if role == "organization":
org_data = {
'org_name': org_name,
'phone': phone,
'country_code': country_code,
'department': department,
'location': location
}
org_id = self.database_manager.create_organization(org_data)
user_data = {
'username': username,
'email': email,
'password': password,
'name': name,
'role': role,
'org_id': org_id
}
else:
# Extract org_id from dropdown selection
org_id = 1 # Default organization for now
user_data = {
'username': username,
'email': email,
'password': password,
'name': name,
'role': role,
'org_id': org_id
}
if self.auth_manager.create_user(user_data):
return {
signup_status: "<div class='status-success'>✅ Account created successfully! Please login.</div>"
}
else:
return {
signup_status: "<div class='status-error'>❌ Failed to create account. Username or email may already exist.</div>"
}
except Exception as e:
return {
signup_status: f"<div class='status-error'>❌ Error: {str(e)}</div>"
}
def handle_analysis(patient_name, patient_age, patient_gender, wound_location, wound_duration,
pain_level, moisture_level, infection_signs, diabetic_status, previous_treatment,
medical_history, medications, allergies, additional_notes, wound_image):
try:
if not wound_image:
return "<div class='status-error'>❌ Please upload a wound image for analysis.</div>"
# Show loading state
loading_html = """
<div style="text-align:center; padding: 30px;">
<div style="display:inline-block; border:4px solid #3182ce; border-radius:50%; border-top-color:transparent; width:40px; height:40px; animation:spin 1s linear infinite;"></div>
<p style="margin-top:15px; color:#3182ce; font-weight:600;">Processing wound analysis...</p>
<style>@keyframes spin {0% {transform:rotate(0deg)} 100% {transform:rotate(360deg)}}</style>
</div>
"""
# 1. Construct questionnaire dictionary for AIProcessor
questionnaire_data = {
'user_id': self.current_user.get('id'),
'age': patient_age,
'diabetic': 'Yes' if diabetic_status != 'Non-diabetic' else 'No',
'allergies': allergies,
'date_of_injury': 'Unknown', # Not collected in this form
'professional_care': 'Yes', # Assumed since using professional interface
'oozing_bleeding': 'None', # Could be mapped from infection_signs
'infection': 'Yes' if infection_signs != 'None' else 'No',
'moisture': moisture_level,
# Additional fields for comprehensive analysis
'patient_name': patient_name,
'patient_gender': patient_gender,
'wound_location': wound_location,
'wound_duration': wound_duration,
'pain_level': pain_level,
'previous_treatment': previous_treatment,
'medical_history': medical_history,
'medications': medications,
'additional_notes': additional_notes
}
# 2. Save questionnaire in DB first
questionnaire_id = self.database_manager.save_questionnaire(questionnaire_data)
# 3. Run AI analysis using the AIProcessor class
try:
logging.info(f"Starting AI analysis for image: {wound_image}")
# Use the AIProcessor analyze_wound method
analysis_result = self.wound_analyzer.analyze_wound(wound_image, questionnaire_data)
if not analysis_result.get('success', False):
raise Exception(analysis_result.get('error', 'Analysis failed for unknown reason'))
# 4. Save AI analysis result to database
self.database_manager.save_analysis_result(questionnaire_id, analysis_result)
# 5. Format comprehensive analysis results with all images
formatted_analysis = self._format_comprehensive_analysis_results(
analysis_result, wound_image, questionnaire_data
)
return formatted_analysis
except Exception as analysis_error:
logging.error(f"AI analysis error: {analysis_error}")
return f"""
<div class='status-error' style='padding: 20px; background: #ffeeee; border-left: 5px solid #ff5555; margin: 20px 0;'>
<h3>❌ Analysis Error</h3>
<p>There was an error analyzing the wound image:</p>
<pre style='background: #f5f5f5; padding: 10px; border-radius: 5px;'>{str(analysis_error)}</pre>
<p>Please try again with a different image or contact support.</p>
</div>
"""
except Exception as e:
logging.error(f"Analysis handler error: {e}")
return f"<div class='status-error'>❌ Analysis failed: {str(e)}</div>"
def handle_logout():
self.current_user = {}
return {
auth_panel: gr.update(visible=True),
practitioner_panel: gr.update(visible=False)
}
def toggle_role_fields(role):
if role == "organization":
return {
org_fields: gr.update(visible=True),
prac_fields: gr.update(visible=False)
}
else:
return {
org_fields: gr.update(visible=False),
prac_fields: gr.update(visible=True)
}
def load_patient_history():
try:
user_id = self.current_user.get('id')
if not user_id:
return "<div class='status-error'>❌ Please login first.</div>"
history_data = self.patient_history_manager.get_user_patient_history(user_id)
formatted_history = self.patient_history_manager.format_history_for_display(history_data)
return formatted_history
except Exception as e:
logging.error(f"Error loading patient history: {e}")
return f"<div class='status-error'>❌ Error loading history: {str(e)}</div>"
def search_specific_patient(patient_name):
try:
user_id = self.current_user.get('id')
if not user_id:
return "<div class='status-error'>❌ Please login first.</div>"
if not patient_name.strip():
return "<div class='status-warning'>⚠️ Please enter a patient name to search.</div>"
patient_data = self.patient_history_manager.search_patient_by_name(user_id, patient_name.strip())
if patient_data:
formatted_data = self.patient_history_manager.format_patient_data_for_display(patient_data)
return formatted_data
else:
return f"<div class='status-warning'>⚠️ No records found for patient: {patient_name}</div>"
except Exception as e:
logging.error(f"Error searching patient: {e}")
return f"<div class='status-error'>❌ Error searching patient: {str(e)}</div>"
# Bind event handlers
login_btn.click(
handle_login,
inputs=[login_username, login_password],
outputs=[auth_panel, practitioner_panel, login_status]
)
signup_btn.click(
handle_signup,
inputs=[signup_username, signup_email, signup_password, signup_name, signup_role,
org_name, phone, country_code, department, location, organization_dropdown],
outputs=[signup_status]
)
signup_role.change(
toggle_role_fields,
inputs=[signup_role],
outputs=[org_fields, prac_fields]
)
analyze_btn.click(
handle_analysis,
inputs=[patient_name, patient_age, patient_gender, wound_location, wound_duration,
pain_level, moisture_level, infection_signs, diabetic_status, previous_treatment,
medical_history, medications, allergies, additional_notes, wound_image],
outputs=[analysis_output]
)
logout_btn_prac.click(
handle_logout,
outputs=[auth_panel, practitioner_panel]
)
history_btn.click(
load_patient_history,
outputs=[patient_history_output]
)
search_patient_btn.click(
search_specific_patient,
inputs=[search_patient_name],
outputs=[specific_patient_output]
)
return app
def _format_comprehensive_analysis_results(self, analysis_result, image_url=None, questionnaire_data=None):
"""Format comprehensive analysis results with all visualization images from AIProcessor."""
try:
# Extract the core analysis results from AIProcessor
success = analysis_result.get('success', False)
if not success:
error_msg = analysis_result.get('error', 'Unknown error')
return f"<div class='status-error'>❌ Analysis failed: {error_msg}</div>"
visual_analysis = analysis_result.get('visual_analysis', {})
report = analysis_result.get('report', '')
saved_image_path = analysis_result.get('saved_image_path', '')
# Extract wound metrics
wound_type = visual_analysis.get('wound_type', 'Unknown')
length_cm = visual_analysis.get('length_cm', 0)
breadth_cm = visual_analysis.get('breadth_cm', 0)
area_cm2 = visual_analysis.get('surface_area_cm2', 0)
detection_confidence = visual_analysis.get('detection_confidence', 0)
# Get image paths for visualizations
detection_image_path = visual_analysis.get('detection_image_path', '')
segmentation_image_path = visual_analysis.get('segmentation_image_path', '')
original_image_path = visual_analysis.get('original_image_path', '')
# Convert images to base64 for embedding
original_image_base64 = None
detection_image_base64 = None
segmentation_image_base64 = None
# Original uploaded image
if image_url and os.path.exists(image_url):
original_image_base64 = self.image_to_base64(image_url)
elif original_image_path and os.path.exists(original_image_path):
original_image_base64 = self.image_to_base64(original_image_path)
elif saved_image_path and os.path.exists(saved_image_path):
original_image_base64 = self.image_to_base64(saved_image_path)
# Detection visualization
if detection_image_path and os.path.exists(detection_image_path):
detection_image_base64 = self.image_to_base64(detection_image_path)
# Segmentation visualization
if segmentation_image_path and os.path.exists(segmentation_image_path):
segmentation_image_base64 = self.image_to_base64(segmentation_image_path)
# Generate risk assessment from questionnaire data
risk_assessment = self._generate_risk_assessment(questionnaire_data)
risk_level = risk_assessment['risk_level']
risk_score = risk_assessment['risk_score']
risk_factors = risk_assessment['risk_factors']
# Set risk class for styling
risk_class = "low"
if risk_level.lower() == "moderate":
risk_class = "moderate"
elif risk_level.lower() == "high":
risk_class = "high"
# Format risk factors
risk_factors_html = "<ul>" + "".join(f"<li>{factor}</li>" for factor in risk_factors) + "</ul>" if risk_factors else "<p>No specific risk factors identified.</p>"
# Create image gallery
image_gallery_html = ""
if original_image_base64 or detection_image_base64 or segmentation_image_base64:
image_gallery_html = '<div class="image-gallery">'
if original_image_base64:
image_gallery_html += f'''
<div class="image-item">
<img src="{original_image_base64}" alt="Original Wound Image">
<h4>📸 Original Wound Image</h4>
<p>Uploaded image for analysis</p>
</div>
'''
if detection_image_base64:
image_gallery_html += f'''
<div class="image-item">
<img src="{detection_image_base64}" alt="Wound Detection">
<h4>🎯 Wound Detection</h4>
<p>AI-detected wound boundaries with {detection_confidence:.1%} confidence</p>
</div>
'''
if segmentation_image_base64:
image_gallery_html += f'''
<div class="image-item">
<img src="{segmentation_image_base64}" alt="Wound Segmentation">
<h4>📏 Wound Segmentation</h4>
<p>Detailed wound area measurement and analysis</p>
</div>
'''
image_gallery_html += '</div>'
# Convert markdown report to HTML
report_html = ""
if report:
report_html = self.markdown_to_html(report)
# Final comprehensive HTML output
html_output = f"""
<div style="max-width: 1200px; margin: 0 auto; background: white; border-radius: 16px; box-shadow: 0 8px 32px rgba(0,0,0,0.1); overflow: hidden;">
<div style="background: linear-gradient(135deg, #3182ce 0%, #2c5aa0 100%); color: white; padding: 40px; text-align: center;">
<h1 style="margin: 0; font-size: 32px; font-weight: 700;">🔬 SmartHeal AI Comprehensive Analysis</h1>
<p style="margin: 15px 0 0 0; opacity: 0.9; font-size: 18px;">Advanced Computer Vision & Medical AI Assessment</p>
<div style="background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; margin-top: 20px;">
<p style="margin: 0; font-size: 16px;"><strong>Patient:</strong> {questionnaire_data.get('patient_name', 'Unknown')} | <strong>Analysis Date:</strong> {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}</p>
</div>
</div>
<div style="padding: 40px;">
<div class="status-success" style="margin-bottom: 30px;">
<strong>✅ Analysis Status:</strong> Analysis completed successfully with comprehensive wound assessment
</div>
<!-- Image Gallery Section -->
<div style="margin-bottom: 40px;">
<h2 style="color: #2d3748; font-size: 24px; margin-bottom: 20px; border-bottom: 2px solid #e53e3e; padding-bottom: 10px;">🖼️ Visual Analysis Gallery</h2>
{image_gallery_html}
</div>
<!-- Wound Detection & Classification -->
<div style="background: #f8f9fa; padding: 30px; border-radius: 12px; margin-bottom: 30px;">
<h2 style="color: #2d3748; margin-top: 0;">🔍 Wound Detection & Classification</h2>
<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 20px; margin: 20px 0;">
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #3182ce; margin: 0 0 10px 0;">Wound Type</h3>
<p style="font-weight: 600; font-size: 18px; color: #2d3748; margin: 0;">{wound_type}</p>
</div>
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #3182ce; margin: 0 0 10px 0;">Detection Confidence</h3>
<p style="font-weight: 600; font-size: 18px; color: #2d3748; margin: 0;">{detection_confidence:.1%}</p>
</div>
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #3182ce; margin: 0 0 10px 0;">Location</h3>
<p style="font-weight: 600; font-size: 18px; color: #2d3748; margin: 0;">{questionnaire_data.get('wound_location', 'Not specified')}</p>
</div>
</div>
</div>
<!-- Wound Measurements -->
<div style="background: #e7f5ff; padding: 30px; border-radius: 12px; margin-bottom: 30px;">
<h2 style="color: #2d3748; margin-top: 0;">📏 Wound Measurements</h2>
<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(150px, 1fr)); gap: 20px; margin: 20px 0;">
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #e53e3e; margin: 0 0 10px 0;">Length</h3>
<p style="font-weight: 700; font-size: 24px; color: #2d3748; margin: 0;">{length_cm:.2f} cm</p>
</div>
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #e53e3e; margin: 0 0 10px 0;">Width</h3>
<p style="font-weight: 700; font-size: 24px; color: #2d3748; margin: 0;">{breadth_cm:.2f} cm</p>
</div>
<div style="background: white; padding: 20px; border-radius: 8px; text-align: center; box-shadow: 0 2px 8px rgba(0,0,0,0.1);">
<h3 style="color: #e53e3e; margin: 0 0 10px 0;">Surface Area</h3>
<p style="font-weight: 700; font-size: 24px; color: #2d3748; margin: 0;">{area_cm2:.2f} cm²</p>
</div>
</div>
</div>
<!-- Risk Assessment -->
<div style="background: #fff4e6; padding: 30px; border-radius: 12px; margin-bottom: 30px;">
<h2 style="color: #2d3748; margin-top: 0;">⚠️ Risk Assessment</h2>
<div style="display: flex; align-items: center; margin: 20px 0; flex-wrap: wrap;">
<div style="background: {'#d4edda' if risk_class == 'low' else '#fff3cd' if risk_class == 'moderate' else '#f8d7da'};
color: {'#155724' if risk_class == 'low' else '#856404' if risk_class == 'moderate' else '#721c24'};
padding: 15px 30px;
border-radius: 30px;
font-weight: 700;
font-size: 20px;
text-transform: uppercase;
letter-spacing: 1px;
margin-right: 20px;
margin-bottom: 10px;">
{risk_level} RISK
</div>
<div style="font-size: 18px; color: #2d3748;">
<strong>Risk Score:</strong> {risk_score}/10
</div>
</div>
<div style="background: white; padding: 25px; border-radius: 8px; margin: 15px 0; box-shadow: 0 2px 8px rgba(0,0,0,0.05);">
<h3 style="margin-top: 0; color: #2d3748;">Identified Risk Factors:</h3>
{risk_factors_html}
</div>
</div>
<!-- Patient Information Summary -->
<div style="background: #f0f8f0; padding: 30px; border-radius: 12px; margin-bottom: 30px;">
<h2 style="color: #2d3748; margin-top: 0;">👤 Patient Information Summary</h2>
<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(250px, 1fr)); gap: 15px;">
<div><strong>Age:</strong> {questionnaire_data.get('age', 'Not specified')} years</div>
<div><strong>Gender:</strong> {questionnaire_data.get('patient_gender', 'Not specified')}</div>
<div><strong>Diabetic Status:</strong> {questionnaire_data.get('diabetic', 'Unknown')}</div>
<div><strong>Pain Level:</strong> {questionnaire_data.get('pain_level', 'Not assessed')}/10</div>
<div><strong>Wound Duration:</strong> {questionnaire_data.get('wound_duration', 'Not specified')}</div>
<div><strong>Moisture Level:</strong> {questionnaire_data.get('moisture', 'Not assessed')}</div>
</div>
{f"<div style='margin-top: 20px;'><strong>Medical History:</strong> {questionnaire_data.get('medical_history', 'None provided')}</div>" if questionnaire_data.get('medical_history') else ""}
{f"<div style='margin-top: 10px;'><strong>Current Medications:</strong> {questionnaire_data.get('medications', 'None listed')}</div>" if questionnaire_data.get('medications') else ""}
{f"<div style='margin-top: 10px;'><strong>Known Allergies:</strong> {questionnaire_data.get('allergies', 'None listed')}</div>" if questionnaire_data.get('allergies') else ""}
</div>
<!-- AI Generated Report -->
{f'<div style="background: #f8f9fa; padding: 30px; border-radius: 12px; margin-bottom: 30px;"><h2 style="color: #2d3748; margin-top: 0;">🤖 AI-Generated Clinical Report</h2><div style="background: white; padding: 25px; border-radius: 8px; box-shadow: 0 2px 8px rgba(0,0,0,0.05);">{report_html}</div></div>' if report_html else ''}
<!-- Important Disclaimers -->
<div style="background: #fff5f5; border: 2px solid #feb2b2; padding: 25px; border-radius: 12px; margin: 30px 0;">
<h3 style="color: #c53030; margin-top: 0;">⚠️ Important Medical Disclaimers</h3>
<ul style="color: #742a2a; line-height: 1.6;">
<li><strong>Not a Medical Diagnosis:</strong> This AI analysis is for informational purposes only and does not constitute medical advice, diagnosis, or treatment.</li>
<li><strong>Professional Consultation Required:</strong> Always consult with qualified healthcare professionals for proper clinical assessment and treatment decisions.</li>
<li><strong>Measurement Accuracy:</strong> All measurements are estimates based on computer vision algorithms and should be verified with clinical tools.</li>
<li><strong>Risk Assessment Limitations:</strong> Risk factors are based on provided information and may not reflect the complete clinical picture.</li>
</ul>
</div>
<!-- Footer -->
<div style="text-align: center; padding: 30px 0; border-top: 2px solid #e2e8f0; margin-top: 30px;">
<p style="color: #6c757d; font-style: italic; font-size: 16px; margin: 0;">
🏥 Analysis completed by <strong>SmartHeal AI</strong> - Advanced Wound Care Assistant<br>
<small>Report generated on {datetime.now().strftime('%B %d, %Y at %I:%M %p')}</small>
</p>
</div>
</div>
</div>
"""
return html_output
except Exception as e:
logging.error(f"Error formatting comprehensive results: {e}")
return f"<div class='status-error'>❌ Error displaying results: {str(e)}</div>"
def _generate_risk_assessment(self, questionnaire_data):
"""Generate risk assessment based on questionnaire data"""
if not questionnaire_data:
return {'risk_level': 'Unknown', 'risk_score': 0, 'risk_factors': []}
risk_factors = []
risk_score = 0
try:
# Age assessment
age = questionnaire_data.get('age', 0)
if isinstance(age, str):
try:
age = int(age)
except ValueError:
age = 0
if age > 65:
risk_factors.append("Advanced age (>65 years)")
risk_score += 2
elif age > 50:
risk_factors.append("Older adult (50-65 years)")
risk_score += 1
# Diabetic status
diabetic_status = str(questionnaire_data.get('diabetic', '')).lower()
if 'yes' in diabetic_status:
risk_factors.append("Diabetes mellitus")
risk_score += 3
# Infection signs
infection = str(questionnaire_data.get('infection', '')).lower()
if 'yes' in infection:
risk_factors.append("Signs of infection present")
risk_score += 3
# Pain level
pain_level = questionnaire_data.get('pain_level', 0)
if isinstance(pain_level, str):
try:
pain_level = float(pain_level)
except ValueError:
pain_level = 0
if pain_level >= 7:
risk_factors.append("High pain level (≥7/10)")
risk_score += 2
elif pain_level >= 5:
risk_factors.append("Moderate pain level (5-6/10)")
risk_score += 1
# Wound duration
duration = str(questionnaire_data.get('wound_duration', '')).lower()
if any(term in duration for term in ['month', 'months', 'year', 'years']):
risk_factors.append("Chronic wound (>4 weeks)")
risk_score += 3
# Moisture level
moisture = str(questionnaire_data.get('moisture', '')).lower()
if any(term in moisture for term in ['wet', 'saturated']):
risk_factors.append("Excessive wound exudate")
risk_score += 1
# Medical history analysis
medical_history = str(questionnaire_data.get('medical_history', '')).lower()
if any(term in medical_history for term in ['vascular', 'circulation', 'heart']):
risk_factors.append("Cardiovascular disease")
risk_score += 2
if any(term in medical_history for term in ['immune', 'cancer', 'steroid']):
risk_factors.append("Immune system compromise")
risk_score += 2
if any(term in medical_history for term in ['smoking', 'tobacco']):
risk_factors.append("Smoking history")
risk_score += 2
# Determine risk level
if risk_score >= 8:
risk_level = "Very High"
elif risk_score >= 6:
risk_level = "High"
elif risk_score >= 3:
risk_level = "Moderate"
else:
risk_level = "Low"
return {
'risk_score': risk_score,
'risk_level': risk_level,
'risk_factors': risk_factors
}
except Exception as e:
logging.error(f"Risk assessment error: {e}")
return {
'risk_score': 0,
'risk_level': 'Unknown',
'risk_factors': ['Unable to assess risk due to data processing error']
} |