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Strategies to Address the Lack of Labeled Data for Supervised Machine Learning Training With Electronic Health Records: Case Study for the Extraction of Symptoms From Clinical Notes
BACKGROUND: Automated extraction of symptoms from clinical notes is a challenging task owing to the multidimensional nature of symptom description. The availability of labeled training data is extremely limited owing to the nature of the data containing protected health information. Natural language...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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JMIR Publications
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961340/ https://www.ncbi.nlm.nih.gov/pubmed/35285805 http://dx.doi.org/10.2196/32903 |