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The 6th International Workshop on Health Natural Language Processing 
(HealthNLP 2023) 

ICHI 2023 workshop | June 26th, 2023 | Houston, Texas, USA
The Conference


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.

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. 

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.


Senior Director

Health Futures

Microsoft Research

Hoifung Poon is Senior Director at Health Futures in Microsoft Research and an affiliated professor at the University of Washington Medical School. He leads biomedical AI research for precision health, with a particular focus on unlocking


population-level real-world evidence (RWE) from patient data to accelerate biomedical research and improve clinical care. He has given tutorials on this topic at top conferences such as the Association for Computational Linguistics (ACL) and the Association for the Advancement of Artificial Intelligence (AAAI). His research spans a wide range of problems in biomedical AI, from biomedical natural language processing (NLP) to multi-modal learning and causal inference, and his prior work has been recognized with Best Paper Awards from premier venues such as the North American Chapter of the Association for Computational Linguistics (NAACL), Empirical Methods in Natural Language Processing (EMNLP), and Uncertainty in AI (UAI). He received his PhD in Computer Science and Engineering from University of Washington, specializing in machine learning and NLP.


Important Dates

  • Deadline for all submissions: March 10th, 2023

  • Notification of decisions:  March 23rd, 2023

  • Deadline for camera-ready papers:  March 30th, 2023

  • Workshop date: June 26th, 2023

important dates

Call for Submissions


HealthNLP will accept both regular papers (4-8 pages, including references) and abstracts (2 pages, including references). Regular papers will describe mature ideas, where a substantial amount of implementation, experimentation, or data collection and analysis has been completed. Abstracts will describe innovative ideas, where preliminary implementation and validation work have been conducted.

Submissions will be handled electronically through EasyChair.  When submitting papers, the authors must select the "HealthNLP Workshop" track. Papers must adhere to the IEEE Proceedings Format and be submitted as a single PDF file. Before a submission is sent to the reviewers, the program chairs will perform an assessment to determine the best fit for the submission.

HealthNLP uses a single-blind two-layer peer reviewing process. The final decision will be made by the program chairs based on at least two reviews by program committee members. All accepted submissions will be presented at the workshop and published in the IEEE ICHI 2023 Proceedings (archived in IEEE Xplore Digital Library).







  • Yifan Peng, Weill Cornell Medicine, US

  • Halil Kilicoglu, University of Illinois at Urbana-Champaign, US

Publication Chair

  • Qingyu Chen, National Library of Medicine, National Institutes of Health, US

Steering committee

  • Sophia Ananiadou, University of Manchester, UK

  • Wendy Chapman, University of Melbourne. AU

  • Dina Demner-Fushman, National Library of Medicine/National Institutes of Health, US

  • Hongfang Liu, Mayo Clinic, US

  • Zhiyong Lu, National Library of Medicine/National Institutes of Health, US

  • Buzhou Tang, Harbin Institute of Technology, CN

  • Özlem Uzuner, George Mason University, US

  • ​Karin Verspoor, RMIT University, AU

  • Hua Xu, University of Texas Health Science Center at Houston, US

Program Committee​

  • Murthy Devarakonda, Novartis, US

  • Carsten Eickhoff, Brown University, US

  • Yadan Fan, Nuance, US

  • Udo Hahn, Friedrich Schiller University Jena, Germany

  • Zhengxing Huang, Zhejiang University, China

  • Lynette Hirschman, MITRE, US

  • Chun-Nan Hsu, University of California San Diego, US

  • Yoshinobu Kano, Shizuoka University, Japan

  • Rohit Kate, University of Wisconsin-Milwaukee, US

  • Dimitrios Kokkinakis, University of Gothenburg, Germany

  • Alberto Lavelli, Fondazione Bruno Kessler, Italy

  • Jianlin Shi, University of Utah, US

  • Manabu Torii, Kaiser Permanente, US

  • Stephen Wu, UTHealth, US

  • Yonghui Wu, University of Florida, US



Please contact if you have any questions.

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