What are the Challenges of Data Fusion in Epidemiology?
While data fusion offers significant benefits, it also presents several challenges: 1. Data Privacy: Protecting sensitive health information while combining data from different sources. 2. Data Quality: Ensuring the reliability and validity of data from diverse origins. 3. Standardization: Harmonizing data formats and terminologies to enable seamless integration. 4. Computational Complexity: Managing the large volume and complexity of integrated data sets. 5. Interdisciplinary Collaboration: Coordinating efforts among epidemiologists, data scientists, and other stakeholders.
