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Can machine learning methods be used for identification of at-risk neonates in low-resource settings? A prospective cohort study
INTRODUCTION: Timely identification of at-risk neonates (ARNs) in the community is essential to reduce mortality in low-resource settings. Tools such as American Academy of Pediatrics pulse oximetry (POx) and WHO Young Infants Clinical Signs (WHOS) have high specificity but low sensitivity to identi...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
BMJ Publishing Group
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10626794/ https://www.ncbi.nlm.nih.gov/pubmed/37918940 http://dx.doi.org/10.1136/bmjpo-2023-002134 |