About: Research on Artificial Intelligence and Primary Care: A Scoping Review

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Research on Artificial Intelligence and Primary Care: A Scoping Review
Creator	Zwarenstein, Merrick Kueper, Jacqueline Lizotte, Daniel Terry, Amanda
Source	MedRxiv
abstract	Objective: The purpose of this study was to assess the nature and extent of the body of research on artificial intelligence (AI) and primary care. Methods: We performed a scoping review, searching 11 published and grey literature databases with subject headings and key words pertaining to the concepts of 1) AI and 2) primary care: MEDLINE, EMBASE, Cinahl, Cochrane Library, Web of Science, Scopus, IEEE Xplore, ACM Digital Library, MathSciNet, AAAI, arXiv. Screening included title and abstract and then full text stages. Final inclusion criteria: 1) research study of any design, 2) developed or used AI, 3) used primary care data and/or study conducted in a primary care setting and/or explicit mention of study applicability to primary care; exclusion criteria: 1) narrative, editorial, or textbook chapter, 2) not applicable to primary care population or settings, 3) full text inaccessible in the English Language. We extracted and summarized seven key characteristics of included studies: overall study purpose(s), author appointments, primary care functions, author intended target end user(s), target health condition(s), location of data source(s) (if any), subfield(s) of AI. Results: Of 5,515 non-duplicate documents, 405 met our eligibility criteria. The body of literature is primarily focused on creating novel AI methods or modifying existing AI methods to support physician diagnostic or treatment recommendations, for chronic conditions, using data from higher income countries. Meaningfully more studies had at least one author with a technology, engineering, or math appointment than with a primary care appointment (57 (14%) compared to 217 (54%)). Predominant AI subfields were supervised machine learning and expert systems. Discussion: Overall, AI research associated with primary care is at an early stage of maturity with respect to widespread implementation in practice settings. For the field to progress, more interdisciplinary research teams with end-user engagement and evaluation studies are needed.
has issue date	2019-08-21(xsd:dateTime)
bibo:doi	10.1101/19003913
has license	medrxiv
sha1sum (hex)	d8080448dd1b7934e9ee738da154ad60fd51e933
schema:url	https://doi.org/10.1101/19003913
resource representing a document's title	Research on Artificial Intelligence and Primary Care: A Scoping Review
resource representing a document's body	covid:d8080448dd1b7934e9ee738da154ad60fd51e933#body_text
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