A clinical text classification paradigm using weak supervision and deep representation

Abstract Background Automatic clinical text classification is a natural language processing (NLP) technology that unlocks information embedded in clinical narratives. Machine learning approaches have been shown to be effective for clinical text classification tasks. However, a successful machine lea...

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Библиографические подробности

Главные авторы:	Yanshan Wang, Sunghwan Sohn, Sijia Liu, Feichen Shen, Liwei Wang, Elizabeth J. Atkinson, Shreyasee Amin, Hongfang Liu
Формат:	Artigo
Язык:	Inglês
Опубликовано:	BMC 2019-01-01
Серии:	BMC Medical Informatics and Decision Making
Предметы:	Clinical text classification Natural language processing Electronic health records Machine learning Weak supervision
Online-ссылка:	http://link.springer.com/article/10.1186/s12911-018-0723-6
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