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Small and imbalanced datasets commonly seen in healthcare represent a challenge when training classifiers based on deep learning models.
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Automated classification of consumer health information needs in patient portal messages
Robert M Cronin, Daniel Fabbri, Joshua C Denny, and Gretchen Purcell Jackson · 2015
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High dimensional data classification and feature selection using support vector machines
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Increasing patient portal usage: preliminary outcomes from the mychart genius project
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Joint embedding of words and labels for text classification
Guoyin Wang, Chunyuan Li, Wenlin Wang, Yizhe Zhang, Dinghan Shen, Xinyuan Zhang, Ricardo Henao, and Lawrence Carin · 2018
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A framework of rebalancing imbalanced healthcare data for rare events’ classification: a case of look-alike sound-alike mix-up incident detection
Yang Zhao, Zoie Shui-Yee Wong, and Kwok Leung Tsui · 2018
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Detecting hypoglycemia incidents reported in patients’ secure messages: Using cost-sensitive learning and oversampling to reduce data imbalance
Jinying Chen, John Lalor, Weisong Liu, Emily Druhl, Edgard Granillo, Varsha G Vimalananda, and Hong Yu · 2019
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A comparison of rule-based and machine learning approaches for classifying patient portal messages
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Why deep-learning ais are so easy to fool
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Patient portal messaging for care coordination: a qualitative study of perspectives of experienced users with chronic conditions
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Clinical decision support systems: From the perspective of small and imbalanced data set
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Artificial intelligence to organize patient portal messages: a journey from an ensemble deep learning text classification to rule-based named entity recognition
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Distilling task-specific knowledge from bert into simple neural networks
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
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