MATLAB Hospital Patient Statistics Analysis

### Hospital Patient Statistics Implementation with MATLAB

In hospital management or public health data analysis, tracking patient visit numbers over specific time periods is a common requirement. Using MATLAB, you can efficiently handle data import, processing, and visualization. Below is the implementation approach:

Data Preparation Assume the data format contains two columns: timestamp (such as date or hour) and corresponding patient count. Use `readtable` function to import Excel/CSV files, or directly define numerical arrays for analysis.

Time Series Processing Convert time columns to `datetime` type for easy aggregation by day, month, or year (using functions like `retime`). For filtering specific periods (e.g., weekdays), extract data through logical indexing operations.

Statistical Calculations Basic statistics: Calculate daily averages/peak values using `mean` and `max` functions. Rolling statistics: Analyze trends within sliding windows using `movmean` for moving averages.

Visualization Presentation Line charts (`plot`) to display patient count changes over time. Histograms (`histogram`) to show distribution patterns of patient numbers. Enhance readability by adding titles and axis labels (e.g., `xlabel('Date')`).

Extended Applications Combine seasonal factors or events (like pandemics) to analyze reasons for patient number fluctuations. Prediction models: Utilize `fitlm` or Machine Learning Toolbox to forecast future patient volumes.

Through these steps, you can quickly generate clear data reports to assist resource allocation or policy decisions.