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A practical model for the identification of congenital cataracts using machine learning
BACKGROUND: Approximately 1 in 33 newborns is affected by congenital anomalies worldwide. We aimed to develop a practical model for identifying infants with a high risk of congenital cataracts (CCs), which is the leading cause of avoidable childhood blindness. METHODS: This case-control study was pe...
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| Pubblicato in: | EBioMedicine |
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| Autori principali: | , , , , , , , , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6948173/ https://ncbi.nlm.nih.gov/pubmed/31901869 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.ebiom.2019.102621 |
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