The implementation of data fusion in epidemiology involves several steps: 1. Data Collection: Gathering data from various sources such as electronic health records, laboratory results, environmental sensors, and social media. 2. Data Cleaning: Ensuring the data is accurate, complete, and free of errors. 3. Data Integration: Merging data sets by aligning them based on common attributes, such as patient ID or geographical location. 4. Data Analysis: Applying statistical methods and machine learning algorithms to analyze the integrated data. 5. Interpretation and Visualization: Presenting the results in a clear and understandable manner, often using data visualization tools.
