Development of message passing-based graph convolutional networks for classifying cancer pathology reports

Development of message passing-based graph convolutional networks for classifying cancer pathology reports

Abstract Background Applying graph convolutional networks (GCN) to the classification of free-form natural language texts leveraged by graph-of-words features (TextGCN) was studied and confirmed to be an effective means of describing complex natural language texts. However, the text classification m...

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Bibliographic Details
Main Authors: Hong-Jun Yoon, Hilda B. Klasky, Andrew E. Blanchard, J. Blair Christian, Eric B. Durbin, Xiao-Cheng Wu, Antoinette Stroup, Jennifer Doherty, Linda Coyle, Lynne Penberthy, Georgia D. Tourassi
Format: Article
Language:English
Published: BMC 2024-09-01
Series:BMC Medical Informatics and Decision Making
Subjects:
Graph
Graph of words
Graph convolutional networks
Message passing networks
Information extraction
Cancer pathology reports
Online Access:https://doi.org/10.1186/s12911-024-02662-5

Internet

https://doi.org/10.1186/s12911-024-02662-5

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