Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes: The 2019 Literature Year in Review

Schultz, M. A., Walden, R. L., Cato, K., Coviak, C. P., Cruz, C., D’Agostino, F., Douthit, B. J., Forbes, T., Gao, G., Lee, M. A., Lekan, D., Wieben, A., & Jeffery, A. D. (2021). Data Science Methods for Nursing-Relevant Patient Outcomes and Clinical Processes. CIN: Computers, Informatics, Nursing, 39(11), 654–667. https://doi.org/10.1097/cin.0000000000000705
Authors:
Mary Anne Schultz
Rachel Lane Walden
Kenrick Cato
Cynthia Peltier Coviak
Christopher Cruz
Fabio D'Agostino
Brian J Douthit
Thompson Forbes
Grace Gao
Mikyoung Angela Lee
Deborah Lekan
Ann Wieben
Alvin D Jeffery
Affiliated Authors:
Mary Anne Schultz
Columbia Affiliation:
Subjects:
Artificial Intelligence (MeSH)
Data Science (MeSH)
Author Keywords:
artificial intelligence
data analytics
nursing research
outcome and process assessment
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Publication Type:
Article
Unique ID:
10.1097/cin.0000000000000705
PMID:
34747890
DOI:
10.1097/cin.0000000000000705
Journal:
Computers, Informatics, Nursing
Publication Date:
Data Source:
PubMed
Source Link:
View PubMed Record
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Record Created: