Cargando…
EPH34 Long COVID Symptoms and Diagnosis in Primary Care: A Cohort Study Using the Thin Database Including Unstructured Text
Autores principales: | Shah, A, Dhalla, S, Subramanian, A, Ford, E, Haroon, S, Kuan, V, Nirantharakumar, K |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Published by Elsevier Inc.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9747514/ http://dx.doi.org/10.1016/j.jval.2022.09.956 |
Ejemplares similares
-
Long Covid symptoms and diagnosis in primary care: A cohort study using structured and unstructured data in The Health Improvement Network primary care database
por: Shah, Anoop D., et al.
Publicado: (2023) -
Learning the Structure of Biomedical Relationships from Unstructured Text
por: Percha, Bethany, et al.
Publicado: (2015) -
FasTag: Automatic text classification of unstructured medical narratives
por: Venkataraman, Guhan Ram, et al.
Publicado: (2020) -
Use of unstructured text in prognostic clinical prediction models: a systematic review
por: Seinen, Tom M, et al.
Publicado: (2022) -
Learning Signals of Adverse Drug-Drug Interactions from the Unstructured Text of Electronic Health Records
por: Iyer, Srinivasan V, et al.
Publicado: ( 201)