Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/84772
Title: Beyond the hype of big data and artificial intelligence : building foundations for knowledge and wisdom
Authors: Car, Josip
Sheikh, Aziz
Wicks, Paul
Williams, Marc S.
Keywords: Big Data
Science::Medicine
Electronic Health Records
Issue Date: 2019
Source: Car, J., Sheikh, A., Wicks, P., & Williams, M. S. (2019). Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom. BMC Medicine, 17(1), 143-. doi:10.1186/s12916-019-1382-x
Series/Report no.: BMC Medicine
Abstract: Big data, coupled with the use of advanced analytical approaches, such as artificial intelligence (AI), have the potential to improve medical outcomes and population health. Data that are routinely generated from, for example, electronic medical records and smart devices have become progressively easier and cheaper to collect, process, and analyze. In recent decades, this has prompted a substantial increase in biomedical research efforts outside traditional clinical trial settings. Despite the apparent enthusiasm of researchers, funders, and the media, evidence is scarce for successful implementation of products, algorithms, and services arising that make a real difference to clinical care. This article collection provides concrete examples of how “big data” can be used to advance healthcare and discusses some of the limitations and challenges encountered with this type of research. It primarily focuses on real-world data, such as electronic medical records and genomic medicine, considers new developments in AI and digital health, and discusses ethical considerations and issues related to data sharing. Overall, we remain positive that big data studies and associated new technologies will continue to guide novel, exciting research that will ultimately improve healthcare and medicine—but we are also realistic that concerns remain about privacy, equity, security, and benefit to all.
URI: https://hdl.handle.net/10356/84772
http://hdl.handle.net/10220/49791
DOI: http://dx.doi.org/10.1186/s12916-019-1382-x
Rights: © 2019 The Author(s). This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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