Disaggregating asthma: Big investigation versus big data.

ABSTRACT: We are facing a major challenge in bridging the gap between identifying subtypes of asthma to understand causal mechanisms and translating this knowledge into personalized prevention and management strategies. In recent years, "big data" has been sold as a panacea for generating hypotheses and driving new frontiers of health care; the idea that the data must and will speak for themselves is fast becoming a new dogma. One of the dangers of ready accessibility of health care data and computational tools for data analysis is that the process of data mining can become uncoupled from the scientific process of clinical interpretation, understanding the provenance of the data, and external validation. Although advances in computational methods can be valuable for using unexpected structure in dat

SUBMITTER: Belgrave D 

PROVIDER: S-EPMC5292995 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature