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DMDA-Health 2014 : PAKDD Workshop on Data Mining and Decision Analytics for Public Health and Wellness | |||||||||||||||
Link: https://sites.google.com/site/dmdahkbu/ | |||||||||||||||
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Call For Papers | |||||||||||||||
PAKDD Workshop on Data Mining and Decision Analytics for Public Health and Wellness
Important Dates Jan. 6, 2014: Paper submission deadline Feb. 5, 2014: Author notification Feb. 19, 2014: Camera-ready due The outstanding papers will be included in a LNCS/LNAI post Proceedings of PAKDD Workshops published by Springer. Aims and Scope For many years, data mining and decision analytics techniques have already been extensively applied to various domains, such as social networks, marketing, and web technology. While the focus of this workshop is mainly on the issues and challenges of data mining techniques with the purpose of improving human well-being and quality of life. It is expected that the workshop may increase the diversity of application areas that can benefit from data mining. At the same time, it is also desirable that the discussion and vision of this workshop would also offer further insights into, as well as new tools for, the issues of data collection, processing, system modeling, simulation and optimization arising from various public health topics. The objective of this workshop is to serve as a venue for researchers to discuss how data mining and analytics methods can contribute to improving public health quality in clinical, medical/biomedical, and healthcare systems in smart ways, including evidence-based medicine, personalized treatment and healthcare, and active surveillance and control of diseases. In addition to mining statistical regularities, associations, or causalities from large-scale health-related datasets, it would be more desirable to further investigate how the results can effectively and efficiently support decision-making, system modeling, optimization, and simulation in various healthcare systems. Topics of Interest o Large-scale data acquisition and management issues for public health o Social and other network-based analysis for public health o Medical big data mining and innovative applications o Mining risk patterns in medical data o Mental and physical health data integration o Biomarker discovery and biomedical data mining o Clinical data mining for practice knowledge building o Data mining from clinical decision-making, and practitioner reflection o Data mining from genetic data of diseases o Data mining for disease profiling and personalized treatment o Data mining for (active) syndromic surveillance o Data mining for infectious/chronic disease epidemiology and control o Data mining for exploring hidden patterns in clinical systems o Data mining for medical/biomedical, and healthcare systems o Spatiotemporal data exploration and mining of diseases o Unstructured data mining in medicine and healthcare o Semantic data mining in medicine and healthcare o Scalable data integration in medicine and healthcare o Evidence-based decision-support systems o Healthcare knowledge abstraction, classification, and summarization o Healthcare knowledge computerization, execution, inference, and representation Submission Information Paper submission system is at https://www.easychair.org/conferences/?conf=dmda2014. We call for original and unpublished research contributions of manuscripts to the workshop following the Springer LNCS/LNAI manuscript submission guidelines (available at http://www.springer.de/comp/lncs/authors.html). Each submitted paper should include an abstract up to 200 words and be not longer than 12 single-spaced pages with 10pt font size. All papers must be submitted electronically through the paper submission system in PDF format only. The submitted paper should NOT adhere to the double-blind review policy. Note: Submitting a paper to the workshop means that if the paper is accepted, at least one author should attend the workshop to present the paper. For no-show authors, their affiliations will receive a notification. Organizers o Jiming Liu, Hong Hong Baptist University o Kwok-Wai William Cheung, Hong Hong Baptist University o Benyun Shi, Hong Hong Baptist University |
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