Big Data and the End of Epidemiology - Patrick Bossuyt -18122019

The arrival of Big Data, in combination with the rise of Machine Learning and Artificial Intelligence, has encouraged some analysts to announce the termination of theory, and the end of the traditional scientific method. By implication, that would be the end of epidemiology as we know it. In the Petabyte era, we are now able to analyze the data without hypotheses about what it might show.

In this presentation, we will analyze the origins and describe the development of Big Data. We will also study more recent obituaries for “Big Data” as a concept, and what the burial of big data means. From there we analyze the claim that the traditional scientific methods have reached their limits and explore the implications of these developments for the practice of epidemiology and the training of future epidemiologists.

Patrick M. Bossuyt is the professor of Clinical Epidemiology at the Amsterdam University Medical Centers, where he leads the Biomarker and Test Evaluation Research program. The BiTE Program aims to develop and appraise methods for evaluating medical tests and biomarkers, and to apply these methods in pragmatic clinical studies. Bossuyt spearheaded the STARD initiative for better reporting of diagnostic accuracy studies. He acted as chair of his Department for ten years, as Dean of Graduate Studies, and as chair of the Division of Public Health and Clinical Methods. He currently chairs the Scientific Advisory Committee of the Dutch Health Insurance Board, which oversees the health care benefits covered in the national health insurance program. Earlier this year, he received the Inspiring Minds Award from the American Association of Clinical Chemistry.