Yearb Med Inform 2014; 23(01): 150-153
DOI: 10.15265/IY-2014-0035
Original Article
Georg Thieme Verlag KG Stuttgart

Sensor, Signal, and Imaging Informatics: Big Data and Smart Health Technologies

S. Voros
1   UJF-Grenoble 1 / CNRS / INSERM, TIMC-IMAG UMR 5525, Grenoble, F-38041, France
,
A. Moreau-Gaudry
1   UJF-Grenoble 1 / CNRS / INSERM, TIMC-IMAG UMR 5525, Grenoble, F-38041, France
2   UJF-Grenoble 1 / CHU / INSERM CIT803, Grenoble, F-38041, France
,
Section Editors for the IMIA Yearbook Section on Sensor, Signal and Imaging Informatics › Author Affiliations
Further Information

Publication History

15 August 2014

Publication Date:
05 March 2018 (online)

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Summary

Objectives: This synopsis presents a selection for the IMIA (International Medical Informatics Association) Yearbook 2014 of excellent research in the broad field of Sensor, Signal, and Imaging Informatics published in the year 2013, with a focus on Big Data and Smart Health Technologies

Methods: We performed a systematic initial selection and a double blind peer review process to find the best papers in this domain published in 2013, from the PubMed and Web of Science databases. A set of MeSH keywords provided by experts was used.

Results: Big Data are collections of large and complex datasets which have the potential to capture the whole variability of a study population. More and more innovative sensors are emerging, allowing to enrich these big databases. However they become more and more challenging to process (i.e. capture, store, search, share, transfer, exploit) because traditional tools are not adapted anymore.

Conclusions: This review shows that it is necessary not only to develop new tools specifically designed for Big Data, but also to evaluate their performance on such large datasets.