How do Machine Learning Algorithms Aid Epidemiologists?
Machine learning algorithms are essential in analyzing large datasets to uncover hidden patterns and correlations that may not be evident through traditional methods. They can be used for predictive modeling, identifying at-risk populations, and even for real-time disease surveillance. For example, supervised learning techniques can predict the likelihood of disease outbreaks based on historical data, while unsupervised learning can group patients with similar symptoms to identify new disease syndromes.
