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The 9th Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH’21) In conjunction with IEEE International Conference on Data Mining (ICDM’21) – Aukland, New Zealand

The 9th Workshop on Data Mining in Biomedical Informatics and Healthcare (DMBIH21)

In conjunction with IEEE International Conference on Data Mining (ICDM21) Aukland, New Zealand, December 7-10, 2021

DESCRIPTION AND CFP

The 9th 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, deep learning and knowledge extraction methods using biomedical image analysis and natural language processing. Submissions are invited to address the need for developing new methods to mine, summarize and integrate the huge volume and diverse modalities of the structured and unstructured biomedical and healthcare data that can potentially lead to significant advances in the field.

Topics of interest include but are not limited to:

  • Classifying and clustering big data in electronic health records (EHRs)
  • Classifying and clustering temporal data in EHRs and biomedical data in high dimensional spaces
  • Application of deep learning methods to clinical data
  • Topic modeling / detection in large amounts of clinical textual data
  • Data preprocessing and cleansing to deal with noise and missing data in large biomedical or population health data sets
  • Algorithms to speed up the analysis of big biomedical data
  • Novel visualization techniques to facilitate the query and analysis of clinical data
  • Statistics and probability in large-scale data mining
  • Evidence-based medicine
  • Medical image data mining
  • HIPAA compliance data mining
  • Pharmacogenomics data mining
  • Biological markers detection
  • Biological and clinical data analysis and integration for translational research
  • Computational genetics, genomics and proteomics

ATTRACTING QUALITY PAPERS

  • The workshop will be advertised on DBWorld, DMBIH’s and other relevant mailing lists, program committee members and previous speakers, and to personal contacts.
  • A best paper award will be delivered.
  • A special issue in a relevant journal will try to be organized.
  • The keynote speaker will be well-known in the field.

PAST WORKSHOPS

This workshop has been held eight times in the past:

  1. IEEE ICDM in Dallas, TX, 2013 (DMBIH’13)
  2. IEEE ICDM in Shenzhen, China, 2014 (DMBIH’14)
  3. IEEE ICDM in Atlantic City, NJ, 2015 (DMBIH’15)
  4. IEEE ICDM in Barcelona, Spain, 2016 (DMBIH’16)
  5. IEEE ICDM in New Orleans, LA, 2017 (DMBIH’17)
  6. IEEE ICDM in Singapore, 2018 (DMBIH’18)
  7. IEEE ICDM in Beijing, China, 2019 (DMBIH’19)
  8. IEEE ICDM in Sorrento, Italy, 2020 (DMBIH’20) (Virtual)

The DMBIH’17 was a full-day event where all the other workshops were held as a half-day event. The DMBIH’17 featured ten paper presentations. The previous workshops (2016 and before) featured six paper presentations each. Our keynote speakers were Dr. Hong Yu from University of Massachusetts in 2013, Dr. Yuan-Ting Zhang from Chinese University of Hong Kong in 2014, Dr. Qing Zeng from University of Utah in 2015, Dr. Paulo Lisboa from Liverpool John Moores University in 2016, and Dr. Kenji Suzuki from Illinois Institute of Technology in 2018, and finally Prof. Jiao Li from Chinese Academy of Medical Sciences in 2019

There were also best paper awards one for each year of which the 2013 award was sponsored by Fresenius Medical Care and the 2017 award was sponsored by both the School of Engineering and Computer Science, Oakland University and the College of Computing and Digital Media, DePaul University. A special issue called “Clinical Data Mining” in the Journal of Computers in Biology and Medicine has been published (as part of Volume 62) for DMBIH’13. More details can be found at the Journal’s website: http://www.sciencedirect.com/science/journal/00104825/62. For DMBIH’14, a special issue on “Mining Big Data in Biomedicine and Health Care” in the Journal of Biomedical Informatics has been published which attracted 35 manuscripts out of which 17 were accepted for publication.

The call for paper is accessible at http://media.journals.elsevier.com/content/files/call-for-papers- special-24093109.pdf. More information about DMBIH’15 workshop can be found at the 2015 workshop’s website at: https://wwwp.oakland.edu/secs/dmbih-workshop-2015. More details about DMBIH’16 workshop can be found at the 2016 workshop’s website at: http://idal.uv.es/dmbih16/. A special issue on “Knowledge Discovery in Biomedicine” in the International Journal of Knowledge Discovery in Bioinformatics (IJKDB) is an ongoing effort to publish the selected papers presented in DMBIH’17 workshop as well as other submissions.

More details about DMBIH’17 workshop can be found at the 2017 workshop’s website at: https://www.oakland.edu/secs/dmbih-workshop-2017

SUBMISSIONS AND PROCEEDINGS

Paper submissions will be done through the IEEE ICDM Workshop CyberChair submission system which can be accessed via this link:

https://wi-lab.com/cyberchair/2020/icdm20/scripts/ws_submit.php?subarea=S

Per ICDM instructions, papers are limited to a maximum of eight pages and should follow the IEEE ICDM format requirements. All accepted workshop papers will be published in 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.

Chair Bio

Dr. Samah Jamal Fodeh, PhD, (Chair) has a dual appointment as associate research scientist at the Yale Center for Medical Informatics (YCMI) at Yale School of Medicine and the Veterans Administration (VA) in West Haven, CT. She received her M.S. and Ph.D. degrees in Computer Science from Michigan State University in 2006 and 2010, respectively. Her research has been supported by NIH and the VA. Her research interests include data mining, machine learning, information retrieval and information extraction.

CONTACT INFORMATION OF THE ORGANIZERS



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Admission

Free

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Conferences and Symposia