Predictive healthcare analytics is revolutionizing the detection and management of disease outbreaks by utilizing advanced technologies such as artificial intelligence (AI), big data, and machine learning (ML). This study examines how data-driven methodologies facilitate the early detection of possible epidemics, boost public health outcomes, and improve response tactics. In order to predict illness trends and reduce risks, it is essential to integrate electronic health records (EHR), real-time monitoring systems, and predictive modelling methods. This study investigates the ways in which data analytics aids in monitoring, forecasting, and managing the spread of illnesses. We'll examine various data sources, methods for analyzing them, and the difficulties in making good use of this knowledge.
Python, ML, Deep Learning, AI.
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