http://icrc.hitsz.edu.cn/CHIP2017/
Introduction:
The International Conference on Health Information Processing (CHIP) is the annual symposium of the CIPS Technical Committee of Medical, Health and Biological Information Processing. CHIP is a leading international conference specialized in the fields of health information processing in China. It serves as a main forum for researchers and practitioners from academia, industry and government all over the world to share their ideas, research results and experiences for further promotion in the fields. The previous CHIP conferences were successfully held in Shenzhen (2015 and 2016). In the first two conferences, experts from USA and China shared their research results and experiences only by oral presentations. In this year, we plan to call for papers to show lastest research results in this domain. All accepted papers will be recommended to the following SCI-indexed journals after the conference.
Call for papers:
The purpose of the third China Conference on Health Information Processing is to bring together researchers and practitioners interested in the application of information technologies to healthcare and medicine in general and to the support of persons with special needs in particular.
Health information processing is one of the most important tasks in the fields of life science and medicine. It has been attracted more and more attentions, and many computational approaches have been developed. There are two main topics in health information processing: medical data mining, and bioinformatics.
For medical data mining, its aim is to utilize information techonlogies (such as text mining, natural lanuge processing, image processing, data mining, machine learning, intelligent decision support systems, ontologies, mobile technologies, etc.) to remanage and reuse health data. Unstructured data is converted into structured data, information of interest is extracted, knowledge is discoveried and well visualized through these techniques.
For bioinformatics, to expedite analyses of increasing number of biological sequences, many machine-learning algorithms have been introduced into computational biology. By using these techniques, protein structures and functions can be identified based on their primary sequences, and genomics functions can also be analyzed via the sequence data, such as promoter identification, enhancer identification, and disease relationship prediction, etc.
To further development of related technology, CHIP encourages authors to submit papers to one of the main topics indicated below, describing original work, including methods, techniques, advanced prototypes, applications, systems, tools or survey papers, reporting research results and/or indicating future directions. Accepted papers will be recommended to some SCI-indexed journals. Acceptance will be based on quality, relevance and originality.
