Deep active learning for classifying cancer pathology reports

Deep active learning for classifying cancer pathology reports

Abstract Background Automated text classification has many important applications in the clinical setting; however, obtaining labelled data for training machine learning and deep learning models is often difficult and expensive. Active learning techniques may mitigate this challenge by reducing the...

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Bibliographic Details
Main Authors: Kevin De Angeli, Shang Gao, Mohammed Alawad, Hong-Jun Yoon, Noah Schaefferkoetter, Xiao-Cheng Wu, Eric B. Durbin, Jennifer Doherty, Antoinette Stroup, Linda Coyle, Lynne Penberthy, Georgia Tourassi
Format: Article
Language:English
Published: BMC 2021-03-01
Series:BMC Bioinformatics
Subjects:
Active learning
Cancer pathology reports
Text classification
Deep learning
Convolutional neural networks
Online Access:https://doi.org/10.1186/s12859-021-04047-1

Internet

https://doi.org/10.1186/s12859-021-04047-1

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