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...

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Detalles Bibliográficos
Autores principales: Humbert-Droz, Marie, Mukherjee, Pritam, Gevaert, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2022
Materias:
Original Paper
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

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8961340/
https://www.ncbi.nlm.nih.gov/pubmed/35285805
http://dx.doi.org/10.2196/32903

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