The two information bases that I zeroed in on utilizing this week were Computer Source and CINAHL. Both are EBSCO host data sets yet Computer Source centers around innovation related data while CINAHL centers around medical services related data. Dependent on my outcomes underneath, I figure I will track down the most data in the CINAHL, or medical care related, information bases.
CINAHL Database
- medical care AND AI (1371 outcomes)
- EHR or Electronic Health Records AND AI (633 outcomes)
- AI in medical care OR man-made brainpower in medical care (493 outcomes)
Computer Source Database
- wellbeing AND AI (355 outcomes)
- EHR AND AI (13 outcomes)
References
Clancy, T. R. (2020). Artificial Intelligence and Nursing: The Future Is Now. JONA: The Journal of Nursing Administration, 50(3), 125–127. https://doi-org.ezproxy.fhsu.edu/10.1097/NNA.0000000000000855
Habli, I., Lawton, T., & Porter, Z. (2020). Artificial intelligence in health care: accountability and safety. Bulletin of the World Health Organization, 98(4), 251–256. https://doi-org.ezproxy.fhsu.edu/10.2471/BLT.19.237487
Panch, T., Szolovits, P., & Atun, R. (2018). Artificial intelligence, machine learning and health systems. Journal of Global Health, 8(2), 1–8. https://doi-org.ezproxy.fhsu.edu/10.7189/jogh.08.020303
Savage, N. (2012). Better Medicine Through Machine Learning. Communications of the ACM, 55(1), 17–19. https://doi-org.ezproxy.fhsu.edu/10.1145/2063176.2063182
Yadav, P., Steinbach, M., Kumar, V., & Simon, G. (2017). Mining Electronic Health Records (EHRs): A Survey. ACM Computing Surveys, 50(6), 1–40. https://doi-org.ezproxy.fhsu.edu/10.1145/3127881