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Reducing False-Positive Results in Newborn Screening Using Machine Learning
Newborn screening (NBS) for inborn metabolic disorders is a highly successful public health program that by design is accompanied by false-positive results. Here we trained a Random Forest machine learning classifier on screening data to improve prediction of true and false positives. Data included...
Uloženo v:
| Vydáno v: | Int J Neonatal Screen |
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| Hlavní autoři: | , , , , , |
| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
MDPI
2020
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| Témata: | |
| On-line přístup: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7080200/ https://ncbi.nlm.nih.gov/pubmed/32190768 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/ijns6010016 |
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