sections/demo_section.html

<section>
    <h2>🔍 What This Demo Does</h2>
    <ul>
        <li><strong>📊 Time Series Visualization</strong><br>Upload your CSV file containing dates and disease mention counts, and visualize the temporal patterns using interactive Plotly charts.</li>
        <li><strong>🔍 Anomaly Detection</strong><br>Choose from multiple detection methods to identify unusual patterns in your time series:
            <ul>
                <li><strong>LSTM:</strong> Uses deep learning to model sequential data and detect anomalies based on deviations from predicted patterns</li>
                <li><strong>ARIMA:</strong> Employs statistical methods to forecast time series and identify anomalies by comparing actual values to predictions</li>
                <li><strong>IQR:</strong> Flags anomalies by identifying data points that fall outside the interquartile range</li>
            </ul>
        </li>
    </ul>
</section>