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Volume 19 Supplement 5

Selected articles from the second International Workshop on Health Natural Language Processing (HealthNLP 2019)

Research

Publication of this supplement has not been supported by sponsorship. Information about the source of funding for publication charges can be found in the individual articles. The articles have undergone the journal's standard peer review process for supplements. YH and HX were not involved in the decision making process of papers they had co-authored or collaborated with and the peer review was handled by one of the other Supplement Editors. No other competing interests were declared.

Xi'an, China10 June 2019

Conference website

Edited by Yanshan Wang, Hua Xu and Ozlem Uzuner.

  1. Lung cancer is the second most common cancer for men and women; the wide adoption of electronic health records (EHRs) offers a potential to accelerate cohort-related epidemiological studies using informatics a...

    Authors: Liwei Wang, Lei Luo, Yanshan Wang, Jason Wampfler, Ping Yang and Hongfang Liu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):239

    Content type: Research

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  2. With the wide application of Electronic Medical Record (EMR) systems, it has become a daily work for doctors using keyboards to input clinical information into the EMR system. Chinese Input Method Engine (IME)...

    Authors: Feihong Yang, Haihong Guo and Jiao Li

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):237

    Content type: Software

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  3. Clinical named entity recognition (CNER) is important for medical information mining and establishment of high-quality knowledge map. Due to the different text features from natural language and a large number...

    Authors: Luqi Li, Jie Zhao, Li Hou, Yunkai Zhai, Jinming Shi and Fangfang Cui

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):235

    Content type: Research

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  4. Extracting useful information from biomedical literature plays an important role in the development of modern medicine. In natural language processing, there have been rigorous attempts to find meaningful rela...

    Authors: Go Eun Heo, Qing Xie, Min Song and Jeong-Hoon Lee

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):240

    Content type: Research

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  5. De-identification is a critical technology to facilitate the use of unstructured clinical text while protecting patient privacy and confidentiality. The clinical natural language processing (NLP) community has...

    Authors: Xi Yang, Tianchen Lyu, Qian Li, Chih-Yin Lee, Jiang Bian, William R. Hogan and Yonghui Wu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):232

    Content type: Research

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  6. To robustly identify synergistic combinations of drugs, high-throughput screenings are desirable. It will be of great help to automatically identify the relations in the published papers with machine learning ...

    Authors: Yueping Sun, Li Hou, Lu Qin, Yan Liu, Jiao Li and Qing Qian

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):234

    Content type: Research

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  7. To detect attributes of medical concepts in clinical text, a traditional method often consists of two steps: named entity recognition of attributes and then relation classification between medical concepts and...

    Authors: Jun Xu, Zhiheng Li, Qiang Wei, Yonghui Wu, Yang Xiang, Hee-Jin Lee, Yaoyun Zhang, Stephen Wu and Hua Xu

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):236

    Content type: Research

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  8. Accurately recognizing rare diseases based on symptom description is an important task in patient triage, early risk stratification, and target therapies. However, due to the very nature of rare diseases, the ...

    Authors: Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng and Qiaozhu Mei

    Citation: BMC Medical Informatics and Decision Making 2019 19(Suppl 5):238

    Content type: Research

    Published on: