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Full-Text Articles in Medicine and Health Sciences
Deep Active Learning For Classifying Cancer Pathology Reports, 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
Deep Active Learning For Classifying Cancer Pathology Reports, 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
School of Public Health Faculty Publications
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 amount of labelled data required to effectively train a model. In this study, we analyze the effectiveness of 11 active learning algorithms on classifying subsite and histology from cancer pathology reports using a Convolutional Neural Network as the text classification model. Results: We compare the performance of each active learning strategy using two differently sized datasets and two different classification tasks. …