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.
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.
Authors: Danilo De Lorenzo; Yoshihiko Koseki; Elena De Momi; Kiyoyuki Chinzei; Allison M Okamura Journal: IEEE Trans Biomed Eng Date: 2012-11-15 Impact factor: 4.538
Authors: Carlos Aguilar; Eric Westman; J-Sebastian Muehlboeck; Patrizia Mecocci; Bruno Vellas; Magda Tsolaki; Iwona Kloszewska; Hilkka Soininen; Simon Lovestone; Christian Spenger; Andrew Simmons; Lars-Olof Wahlund Journal: Psychiatry Res Date: 2013-03-29 Impact factor: 3.222
Authors: David A Clifton; David Wong; Lei Clifton; Sarah Wilson; Rob Way; Richard Pullinger; Lionel Tarassenko Journal: IEEE J Biomed Health Inform Date: 2013-07 Impact factor: 5.772