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== [[SOCR_News | SOCR News & Events]]:  International Statistics Institute, 2019 World Stats Congress, Invited Session (IPS35): Imaging Statistics and Predictive Data Analytics==
== [[SOCR_News | SOCR News & Events]]:  International Statistics Institute==
==2019 World Statistics Congress==
===Invited Session (IPS35): Imaging Statistics and Predictive Data Analytics===

Revision as of 13:03, 15 July 2018

SOCR News & Events: International Statistics Institute

2019 World Statistics Congress

Invited Session (IPS35): Imaging Statistics and Predictive Data Analytics


  • Websites:
  • WSC Program
  • Date: TBD (18 – 23 August 2019)
  • Place: Kuala Lumpur Convention Centre (Kuala Lumpur, Malaysia)
  • Proceedings: The 2019 WSC proceedings will include titles, abstracts, and papers (6 pages)]
  • Timeline:
    • December 1, 2018 - May 31, 2019: All presenters must register and pay registration fees
    • August 1 – November 1, 2018: All presenters must submit abstracts
    • January 15, 2019 – April 15, 2019: All presenters must submit papers. More information on the abstract submission process will follow soon
    • April 15, 2019: Presenters must submit their presentations (PPTX or PDF)
    • August 18 – 23, 2019: All presenters must attend and present their papers at the congress.


Petabytes of imaging, clinical, biospecimen, genetics and phenotypic biomedical data are acquired annually. Tens-of-thousands of new methods and computational algorithms are developed and reported in the literature and thousands of software tools and data analytic services are introduced each year. This Imaging Statistics and Predictive Data Analytics session will include presentations of leading experts in biomedical imaging, computational neuroscience, and statistical learning focused on streamlining big biomedical data methodologies as well as techniques for management, aggregation, manipulation, computational modeling, and statistical inference. The session will blend innovative model-based and model-free techniques for representation, analysis and interpretation of large, heterogeneous, multi-source, incomplete and incongruent imaging and phenotypic data elements.

Session focus

This session will be of interest to many theoretical statisticians and applied biomedical researchers for the following reasons:

  • The digital revolution demands substantial quantitative skills, data-literacy, and analytical competence: Health science doctoral programs need to be revised and expanded to build basic-science (STEM) expertise, emphasize team-science, rely on holistic understanding of biomedical systems and health problems, and amplify dexterous abilities to handle, interrogate and interpret complex multisource information.
  • The amount of newly acquired biomedical imaging data is increasing exponentially. This demands innovative statistical and computational strategies to aggregate, process, and interpret the deluge of imaging, clinical and phenotypic information.
  • Trans-disciplinary training and inter-professional education is critical for ethical and collaborative research involving complex biomedical imaging and health conditions.
  • Exploratory and predictive Big Data analytics is pivotally important and complementary to traditional hypothesis-driven confirmatory analyses.

Session Program

Time Title Presenter
... ... ...


Will be available in 2019...

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