In the past few decades, we have seen exponential growth in clinical narratives and biomedical articles. As a result, the natural language process (NLP) specialized in biomedicine, which can unlock information from text, receives great attention in the biomedical and clinical domains. Many NLP methods and systems have been developed and have shown promising results in various information extraction, information retrieval, and knowledge discovery tasks. These methods and tools have also been successfully applied to facilitate biomedicine research and support healthcare applications. At the same time, the availability and use of health information online have exploded through the use of social media, question-answering and community discussion forums, health-related websites, and biomedical articles. These present additional challenges and opportunities for further development of new methodologies and applications.

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This workshop aims to provide a unique, interdisciplinary, and high-quality platform to bring together researchers and practitioners in healthcare informatics working with health-related free text, and facilitate close interaction among students, scholars, and industry professionals on health NLP challenges. 

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Topics of interest

• NLP methods: any original methodological research, including but not limited to the following areas: named entity recognition, relation extraction, syntactic parsing, word sense disambiguation, semantic role labeling, topic modeling, discourse analysis, question answering, summarization, simplification, and other topics related to health NLP.

• NLP software tools: any general or specific NLP tools for health data such as clinical notes, social media, and biomedical literature.

• NLP applications: uses of NLP for clinical research or operation, examples including pharmacovigilance, clinical decision support, phenotyping, predictive modeling, risk prediction, and social media mining.