A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery-Reference-Cited by-同舟云学术

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A Machine Learning Approach to Predicting Case Duration for Robot-Assisted Surgery

Published:2019-01-05 Issue:2 Volume:43 Page:
ISSN:0148-5598
Container-title:Journal of Medical Systems
language:en
Short-container-title:J Med Syst

Author:

Zhao Beiqun^ORCID,Waterman Ruth S.,Urman Richard D.,Gabriel Rodney A.

Funder

U.S. National Library of Medicine

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)

Link

http://link.springer.com/article/10.1007/s10916-018-1151-y/fulltext.html

Reference24 articles.

1. Cima, R. R., Brown, M. J., Hebl, J. R., Moore, R., Rogers, J. C., Kollengode, A., Amstutz, G. J., Weisbrod, C. A., Narr, B. J., and Deschamps, C., Use of lean and six sigma methodology to improve operating room efficiency in a high-volume tertiary-care academic medical center. J. Am. Coll. Surg. 213:83–92, 2011. https://doi.org/10.1016/j.jamcollsurg.2011.02.009 .

2. Macario, A., What does one minute of operating room time cost? J. Clin. Anesth. 22:233–236, 2010. https://doi.org/10.1016/j.jclinane.2010.02.003 .

3. Eijkemans, M. J., van Houdenhoven, M., Nguyen, T., Boersma, E., Steyerberg, E. W., and Kazemier, G., Predicting the unpredictable. Anesthesiology 112:41–49, 2010. https://doi.org/10.1016/j.jacc.2015.12.063 .

4. Intuitive Surgical (2016) Intuitive Surgical, Inc. 2016 Annual Report

5. Higgins, R. M., Frelich, M. J., Bosler, M. E., and Gould, J. C., Cost analysis of robotic versus laparoscopic general surgery procedures. Surg. Endosc. 31:185–192, 2017. https://doi.org/10.1007/s00464-016-4954-2 .

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