Axes of a revolution: challenges and promises of big data in healthcare

Smadar Shilo, Hagai Rossman, Eran Segal*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

264 Scopus citations

Abstract

Health data are increasingly being generated at a massive scale, at various levels of phenotyping and from different types of resources. Concurrent with recent technological advances in both data-generation infrastructure and data-analysis methodologies, there have been many claims that these events will revolutionize healthcare, but such claims are still a matter of debate. Addressing the potential and challenges of big data in healthcare requires an understanding of the characteristics of the data. Here we characterize various properties of medical data, which we refer to as ‘axes’ of data, describe the considerations and tradeoffs taken when such data are generated, and the types of analyses that may achieve the tasks at hand. We then broadly describe the potential and challenges of using big data in healthcare resources, aiming to contribute to the ongoing discussion of the potential of big data resources to advance the understanding of health and disease.

Original languageEnglish
Pages (from-to)29-38
Number of pages10
JournalNature Medicine
Volume26
Issue number1
DOIs
StatePublished - 1 Jan 2020
Externally publishedYes

Funding

FundersFunder number
Horizon 2020 Framework Programme786344

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