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Special Issue: Health Natural Language Processing

Photo by Markus Spiske on Unsplash

Photo by Markus Spiske on Unsplash

Call for Papers

With the rapid growth of information technology, the necessity for processing massive amounts of health and medical data utilizing advanced information technologies has also grown. A large amount of valuable data exists in natural text such as free diagnosis text, discharge summaries, online health discussions, eligibility criteria of clinical trials, and so on. Natural language processing (NLP) is a field of computer science, artificial intelligence, and computational linguistics concerned with the interactions between computers and human (natural) language texts. NLP aims to provide computer programs with the ability to process and understand unstructured texts. In the health arena, NLP can assist medical decision making by automatically analyzing the commonalities and differences of large amounts of text data and recommend appropriate actions on behalf of domain experts. NLP techniques have proven to be useful in dealing with the information overload in the health and medical domain, eg, aggregation and summarization of patient notes, treatment analyses, information extraction and retrieval on massive discharge summaries, as well as semantic understanding of patient queries.

To that end, the China Conference on Health Information Processing (CHIP) proposes this theme issue, Health Natural Language Processing to contribute to the development of this interdisciplinary research area. CHIP is the annual symposium of the Chinese Information Processing Society of China (CIPS) Technical Committee of Medical, Health and Biological Information Processing. CHIP is a leading international conference specializing in the fields of health information processing in China. It serves as the main forum for researchers and practitioners from academia, industry, and governments all over the world to share their ideas, research results, and experiences. CHIP conferences have been successfully held since 2015. In the last two conferences, experts from USA, Japan, Australia, China, and other parts of the world came together to share their research results, experiences, and most recent achievements with huge success. All submitted papers were carefully reviewed following the commonly-used international review standard. 

CHIP will select the best scored papers and recommended them to the theme issue. In addition, authors not attending CHIP are invited to submit papers fitting with the theme directly to JMIR Medical Informatics. In this issue, selected articles regarding the use of technologies, methodologies, and applications for Natural Language Processing relating to the health and medical field are invited. The theme issue will be expected to show a diversity of new developments in these areas. Authors are encouraged to submit high-quality original research articles mainly describing original research and presenting results that advance state-of-the-art. Viewpoint and review papers are also welcome.

 

Potential topics include but are not limited to the following:

Please prepare your manuscript with the instructions found here: https://www.jmir.org/content/author-instructions.

Submissions should be sent through the online system at https://medinform.jmir.org/author. Authors should choose the section ‘Theme issue 2019: Health Natural Language Processing’ when submitting papers (see FAQ article on how to submit to a theme issue: https://support.jmir.org/hc/en-us/articles/115001429168-How-do-I-submit-to-a-theme-issue-).

Invited/accepted articles with corresponding authors from institutions that are not JMIR institutional members are subject to the regular JMIR Article Processing Fee (APF). For this theme issue, the APF is discounted by 20%. 

Please see the fee schedule for details: https://medinform.jmir.org/about/editorialPolicies#custom0

Schedule

(Estimated dates)

Guest Editors

Tianyong Hao, South China Normal University, China; haoty@m.scnu.edu.cnBuzhou Tang, Harbin Institute of Technology, China; tangbuzhou@hit.edu.cn Zhengxing Huang, Zhejiang University, China; zhengxinghuang@zju.edu.cn