Machine Learning in Epidemiology

Machine learning in epidemiology uses computer algorithms to analyze health data and identify patterns related to disease spread and risk factors. By processing large amounts of information—such as patient records, environmental data, and social factors—these algorithms can help predict outbreaks, assess the effectiveness of interventions, and improve public health responses. Essentially, machine learning enhances our ability to understand complex relationships in health data, enabling researchers and policymakers to make more informed decisions that can ultimately improve population health outcomes.