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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...
Autores principales: | Lu, Chang, Ghoman, Simran K., Cutumisu, Maria, Schmölzer, Georg M. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7518390/ https://www.ncbi.nlm.nih.gov/pubmed/33042905 http://dx.doi.org/10.3389/fped.2020.00544 |
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