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This article delves into the "Methodological Revolution" underway in epidemiology, elucidating the evolving approaches to causation and prediction within the discipline. Traditional criteria for causation, as established by Bradford Hill, are reevaluated in the context of complex diseases, leading to a shift in focus. Concurrently, the rise of predictive modeling, facilitated by advances in computational capabilities and omics technologies, is transforming epidemiological research [1]. The article navigates the challenges and considerations inherent in this methodological revolution, providing a guide for researchers and public health professionals seeking to enhance their understanding of health determinants and improve prediction accuracy.
