Unsupervised Machine Learning Algorithms Examine Healthcare Providers' Perceptions and Longitudinal Performance in a Digital Neonatal Resuscitation Simulator

Background: Frequent simulation-based education is recommended to improve health outcomes during neonatal resuscitation but is often inaccessible due to time, resource, and personnel requirements. Digital simulation presents a potential alternative; however, its effectiveness and reception by health...

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Bibliographic Details
Main Authors: Chang Lu, Simran K. Ghoman, Maria Cutumisu, Georg M. Schmölzer
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Pediatrics
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fped.2020.00544/full