Deep Learning-Based Natural Language Processing in Radiology: The Impact of Report Complexity, Disease Prevalence, Dataset Size, and Algorithm Type on Model Performance

In radiology, natural language processing (NLP) allows the extraction of valuable information from radiology reports. It can be used for various downstream tasks such as quality improvement, epidemiological research, and monitoring guideline adherence. Class imbalance, variation in dataset size, var...

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Detalles Bibliográficos
Autores principales: Olthof, A. W., van Ooijen, P. M. A., Cornelissen, L. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2021
Materias:
Systems-Level Quality Improvement
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416876/
https://www.ncbi.nlm.nih.gov/pubmed/34480231
http://dx.doi.org/10.1007/s10916-021-01761-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8416876/
https://www.ncbi.nlm.nih.gov/pubmed/34480231
http://dx.doi.org/10.1007/s10916-021-01761-4

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