Journal
Journal of Laboratory and Precision Medicine
Publication Date
2023
Volume
8
First Page
29
Document Type
Open Access Publication
DOI
10.21037/jlpm-23-9
Rights and Permissions
Spies NC, Farnsworth CW, Jackups R, Zaydman MA. Machine learning pipelines developed for the prediction of cancelation of inappropriate parathyroid hormone-related peptide orders demonstrate poor performance in predicting provider behavior. J Lab Precis Med 2023;8:29. doi: 10.21037/jlpm-23-9 This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.
Recommended Citation
Spies, Nicholas C.; Farnsworth, Christopher W.; Jackups, Ronald; and Zaydman, Mark A., "Machine learning pipelines developed for the prediction of cancelation of inappropriate parathyroid hormone-related peptide orders demonstrate poor performance in predicting provider behavior." Journal of Laboratory and Precision Medicine. 8, 29 (2023).
https://digitalcommons.wustl.edu/oa_4/3850
Department
ICTS (Institute of Clinical and Translational Sciences)
Additional Links
Supplemental material is available for this article at publisher site.
