Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom.

Publication date: Jul 17, 2019

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.

Open Access PDF

Car, J., Sheikh, A., Wicks, P., and Williams. Beyond the hype of big data and artificial intelligence: building foundations for knowledge and wisdom. 06550. 2019 BMC Med (17):1.

Concepts Keywords
AI Medical algorithm
Artificial Intelligence Transaction processing
Big Data Artificial intelligence
Biomedical Technology forecasting
BMC Data management
Clinical Trial Big data
Concrete Academic disciplines
Digital Health Technology
Equity Health informatics
Genomic Medicine Articles
Healthcare Data healthcare
Medicine Healthcare
Population Health Artificial intelligence
Privacy

Semantics

Type Source Name
disease MESH privacy
drug DRUGBANK Nonoxynol-9
disease MESH cardiac arrest
disease MESH hypoxia
disease MESH single person
disease MESH community
disease MESH Development
pathway REACTOME Translation
disease MESH NAFLD
disease MESH diagnosis
disease MESH gout
disease MESH stroke
drug DRUGBANK Isoxaflutole
disease MESH alcoholic fatty liver
disease MESH Death
disease MESH uncertainty
drug DRUGBANK Coenzyme M

Similar

Original Article

Leave a Comment

Your email address will not be published. Required fields are marked *