SOCR News ISI WSC IPS35 2019
SOCR News & Events: International Statistics Institute (ISI)
2019 World Statistics Congress (WSC)
Invited Paper Session (IPS35): Imaging Statistics and Predictive Data Analytics
- International Statistics Institute (ISI),
- 2019 World Stats Congress (WSC),
- Session (IPS35): Imaging Statistics and Predictive Data Analytics, 2-hour session including five 20+5 minute talks
- 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)
- August 1 – November 1, 2018: All presenters must submit abstracts
- December 1, 2018 - May 31, 2019: All presenters must register and pay registration fees
- January 15, 2019 – April 15, 2019: All presenters must submit papers. More information on the abstract submission process
- 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.
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.
|...||Predictive Analytics of Big Neuroscience Data||Ivo D Dinov||SOCR, University of Michigan|
|...||Large Brain Network Data Modeling using Deep Learning and Statistical Inference||Eric Tatt Wei Ho||Universiti Teknologi PETRONAS (UTP), Malaysia|
|...||TBD||[ Yunjin Choi]||National University of Singapore|
Will be available in 2019...
- SOCR Home page: http://www.socr.umich.edu
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