Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review
- Journal
- JMIR Human Factors
In The Last Decade
doi.org/10.2196/48633 →Countries where authors are citing Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review
This map shows the geographic impact of Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review more than expected).
Fields of papers citing Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review
This network shows the impact of Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review.
About Barriers to and Facilitators of Artificial Intelligence Adoption in Health Care: Scoping Review
This paper, published in 2024, received 81 indexed citations . Written by André Kushniruk and Elizabeth M. Borycki covering the research area of Health Informatics, Epidemiology and Health Information Management. It is primarily cited by scholars working on Health Informatics (46 citations), Artificial Intelligence (13 citations) and Radiology, Nuclear Medicine and Imaging (13 citations). Published in JMIR Human Factors.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.
This paper is also available at doi.org/10.2196/48633.