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<h2>π What This Demo Does</h2>
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<li><strong>π 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>π 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>
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