DMBIH’18: The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare Singapore, Malaysia, November 17-20, 2018 |
Conference website | http://facweb.cs.depaul.edu/research/vc/ICDM18/index.html |
Submission deadline | August 14, 2018 |
The Sixth Workshop on Data Mining in Biomedical Informatics and Healthcare aims to provide a forum for data miners, informacists, data scientists, and clinical researchers to share their latest investigations in applying data mining techniques to biomedical and healthcare data. The increasing availability of large and complex data sets to the research community, triggers the need to develop more advanced and sophisticated data analytical techniques to exploit and manage these big data. The broader context of the workshop comprehends artificial intelligence, information retrieval, machine learning, and knowledge extraction methods using biomedical image analysis and natural language processing.
Submission Guidelines
Paper submissions will be done through the IEEE ICDM Workshop CyberChair submission system. As per ICDM instructions, papers are limited to a maximum of ten pages, and follow the IEEE ICDM format requirements. All accepted workshop papers will be published in a formal proceedings by the IEEE Computer Society Press. One paper will be selected for the best paper award, which will be awarded at the workshop. Submitted papers must represent original unpublished research that is not currently under review for any other conference or journal. Papers not following these guidelines will be rejected without review and further action may be taken, including (but not limited to) notifications sent to the heads of the institutions of the authors and sponsors of the conference. Submissions received after the due date, exceeding length limit, or not appropriately structured may also not be considered. Authors may contact the conference General Chairs for more information.
List of Topics
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Classifying and clustering big data in electronic health records (EHRs)
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Classifying and clustering temporal data in EHRs and biomedical data in high dimensional spaces
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Application of deep learning methods to clinical data
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Topic modeling / detection in large amounts of clinical textual data
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Data preprocessing and cleansing to deal with noise and missing data in large biomedical or population health data sets
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Algorithms to speed up the analysis of big biomedical data
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Novel visualization techniques to facilitate the query and analysis of clinical data
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Statistics and probability in large-scale data mining
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Evidence-based medicine
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Developing efficient computational algorithms for mining/analyzing big EHR data
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Novel visualization techniques to facilitate the query and analysis of clinical data
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Statistics and probability in large-scale EHR data mining
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Medical image data mining
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HIPAA compliance data mining
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Pharmacogenomics data mining
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Biological markers detection
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Biological and clinical data analysis and integration for translational research
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Computational genetics, genomics and proteomics
Organizing committee
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Daniela Stan Raicu, DePaul University
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Samah Jamal Fodeh, Yale University
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Mohammad-Reza Siadat, Oakland University
- José D. Martín-Guerrero, University of Valencia
Invited Speakers
To Be Announced .....
Publication
DMBIH’18 proceedings will be published in ICDM and are invited for publication in a special issue of the IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Contact
All questions about submissions should be emailed to Stan Raicu, Daniela <draicu@cdm.depaul.edu> or Mohammad Siadat <siadat@oakland.edu>