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

• Published in: Yearbook of medical informatics Vol. 23; no. 1; pp. 150 - 153
• Main Authors: Voros, S., Moreau-Gaudry, A.
• Format: Journal Article
• Language: English; German
• Published: Stuttgart Schattauer Verlag für Medizin und Naturwissenschaften 15.08.2014; Georg Thieme Verlag KG; Schattauer; Schattauer GmbH
• Series: IMIA Yearbook of Medical Informatics: Big Data - Smart Health Technologies
• Subjects: Big data; Computer Science; Data Mining; Datasets as Topic; Engineering Sciences; Humans; Life Sciences; Medical Imaging; Medical Informatics; Original Article; Remote Sensing Technology; Signal and Image Processing; smart health technologies; Big data; smart health technologies
• ISSN: 0943-4747; 2364-0502
• DOI: 10.15265/IY-2014-0035

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.