Automatic extraction of cancer registry reportable information from free-text pathology reports using multitask convolutional neural networks

OBJECTIVE: We implement 2 different multitask learning (MTL) techniques, hard parameter sharing and cross-stitch, to train a word-level convolutional neural network (CNN) specifically designed for automatic extraction of cancer data from unstructured text in pathology reports. We show the importance...

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Detalles Bibliográficos
Autores principales: Alawad, Mohammed, Gao, Shang, Qiu, John X, Yoon, Hong Jun, Blair Christian, J, Penberthy, Lynne, Mumphrey, Brent, Wu, Xiao-Cheng, Coyle, Linda, Tourassi, Georgia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Research and Applications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489089/
https://www.ncbi.nlm.nih.gov/pubmed/31710668
http://dx.doi.org/10.1093/jamia/ocz153

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7489089/
https://www.ncbi.nlm.nih.gov/pubmed/31710668
http://dx.doi.org/10.1093/jamia/ocz153

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