Presented By: Michigan Institute for Data Science
Data Science and Natural Language Processing to Find Rare Classes of Entities From Text
Lead Presenter: VG Vinod Vydiswaran, Assistant Professor, Learning Health Sciences and School of Information, University of Michigan
Natural language processing (NLP) and Data Science methods, including recently popular deep learning-based approaches, can unlock information from narrative text and have received great attention in the medical domain. Many NLP methods have been developed and showed promising results in various information extraction tasks, especially for rare classes of named entities. These methods have also been successfully applied to facilitate clinical research. In this workshop, we will highlight some methods and technologies to identify rare concepts and entities in text in the medical domain as well as other “open” domains.
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