Data Science Priorities for a University Hospital-Based Institute of Infectious Diseases: A Viewpoint

Abstract

Automation of laboratory tests, bioinformatic analysis of biological sequences, and professional data management are used routinely in a modern university hospital-based infectious diseases institute. This dates back to at least the 1980s. However, the scientific methods of this 21st century are changing with the increased power and speed of computers, with the "big data" revolution having already happened in genomics and environment, and eventually arriving in medical informatics. The research will be increasingly "data driven," and the powerful machine learning methods whose efficiency is demonstrated in daily life will also revolutionize medical research. A university-based institute of infectious diseases must therefore not only gather excellent computer scientists and statisticians (as in the past, and as in any medical discipline), but also fully integrate the biologists and clinicians with these computer scientists, statisticians, and mathematical modelers having a broad culture in machine learning, knowledge representation, and knowledge discovery.

Keywords: epidemics; epidemiology; modeling; surveillance.