Before and After: Machine learning for perioperative patient care
- URL: http://arxiv.org/abs/2201.08095v1
- Date: Thu, 20 Jan 2022 09:55:12 GMT
- Title: Before and After: Machine learning for perioperative patient care
- Authors: Iuliia Ganskaia and Stanislav Abaimov
- Abstract summary: Cross-disciplinary review aims to build a bridge between computer science and nursing.
It outlines and classifies the methods for machine learning and data processing in patient care before and after the operation.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: For centuries nursing has been known as a job that requires complex manual
operations, that cannot be automated or replaced by any machinery. All the
devices and techniques have been invented only to support, but never fully
replace, a person with knowledge and expert intuition. With the rise of
Artificial Intelligence and continuously increasing digital data flow in
healthcare, new tools have arrived to improve patient care and reduce the
labour-intensive work conditions of a nurse.
This cross-disciplinary review aims to build a bridge over the gap between
computer science and nursing. It outlines and classifies the methods for
machine learning and data processing in patient care before and after the
operation. It comprises of Process-, Patient-, Operator-, Feedback-, and
Technology-centric classifications. The presented classifications are based on
the technical aspects of patient case.
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