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Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
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File: /var/www/html/application/helpers/my_audit_helper.php
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Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
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Function: getPubMedXML
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Function: pubMedSearch_Global
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Function: require_once
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File: /var/www/html/application/controllers/Detail.php
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File: /var/www/html/application/controllers/Detail.php
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Function: pubMedGetRelatedKeyword
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Aims: To describe machine learning applications in an operating room setting, raise awareness of the lack of nursing inclusion on machine learning algorithm development, and show how operating room nurses can co-create this new technology.
Background: Operating room nurses and managers perform anticipatory work on a daily basis to manage intrinsic and extrinsic factors that can cause surgical delays.
Evaluation: Recent literature on machine learning and its potential use in operating room settings was reviewed along with literature on the role of the nurse in co-creating novel technology.
Key Issue: Machine learning technology is rapidly evolving and being created for the operating room environment to improve patient safety and flow. Operating room nurses and managers are not being included in the development of machine learning algorithms, meaning products may be created that are not usable for all members of the surgical team.
Conclusion: This commentary highlights the ways machine learning effectively assists nurses and nursing managers, suggesting a pathway forward for surgical nursing as co-creators and implementers.
Implication For Nursing Management: Nursing managers will be exposed to machine learning programmes in the near future and need to understand the benefits they have for patient safety and patient flow.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1111/jonm.13736 | DOI Listing |
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