Difference between revisions of "SOCR News DCMB ToolsTechSeminar 2020"
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* Present the Spacekime analytical approach for longitudinal high-dimensional, and heterogeneous biomedical datasets and health case-studies | * Present the Spacekime analytical approach for longitudinal high-dimensional, and heterogeneous biomedical datasets and health case-studies | ||
* Provide hands-on experience with using [https://github.com/SOCR/TCIU R-based spacekime tools and web-services]. Attendees are encouraged to bring their R-enabled laptops and their own data | * Provide hands-on experience with using [https://github.com/SOCR/TCIU R-based spacekime tools and web-services]. Attendees are encouraged to bring their R-enabled laptops and their own data | ||
| − | * | + | * Present some open math problems, computational algorithmic barriers, and data science challenges. |
== Discussion Topics == | == Discussion Topics == | ||
Revision as of 08:14, 7 July 2020
Contents
SOCR News & Events: Spacekime Analytics
The DCMB Tools and Technology Seminar Series highlights tools and nascent technologies that are under development or in current use and are of interest to UM R&D community. These seminars are streamed live, using BlueJeans Events, and are also archived and made available for future viewing via video streaming via the below video archive which links to the DCMB YouTube Chanel.
Logistics
- DCMB Tools and Technology Seminar Series
- Date/Times: Thursday, October 15, 2020, 12 Noon (ET)
- Place: 2036 Palmer Commons
- Title: Spacekime Analytics
- Presenter: Ivo Dinov
Objectives
- Offer a number of "open-science" resources for data science and predictive health analytics
- Present the Spacekime analytical approach for longitudinal high-dimensional, and heterogeneous biomedical datasets and health case-studies
- Provide hands-on experience with using R-based spacekime tools and web-services. Attendees are encouraged to bring their R-enabled laptops and their own data
- Present some open math problems, computational algorithmic barriers, and data science challenges.
Discussion Topics
- Data Science & Predictive Analytics (DSPA) Skills (10-min)
- Overview of SOCR capabilities, resources, and expertise (10-min)
- Hands-on Practice, Try-It-Now, apply to new data (20-min)
- Suggestions, comments, questions, critiques, etc. (10-min)
- Participants should bring laptops, and datasets, to try some of the hands-on resources before, during, and after the training workshop
- URL: https://wiki.socr.umich.edu/index.php/SOCR_News_DCMB_ToolsTechSeminar_2020.
Background
- SOCR News & Events
- SOCR Global Users
- SOCR Navigators
- SOCR Datasets and Challenging Case-studies
- Electronic Textbooks:
Demos
- General SOCR Webapps
- SOCR BrainViewer
- Motion Charts webapp (try it with your own high-dimensional longitudinal data, e.g., Ozone Data)
- Hands-on interactive visualization of extremely high-dimensional data (learning module and webapp)
- Predicting Hospitalization-based Pressure Injuries (webapp)
- Virtual Hospital and Simulated Patient EHR Data (webapp)
References
- This breakout section is sponsored in part by NIH Grants P30 DK089503, P20 NR015331, R01CA233487, and R01MH121079, as well as, NSF Grants 1916425, 1734853 and 1636840.
- Dinov, ID and Velev, MV (2021) Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics, De Gruyter (STEM Series), Berlin/Boston, ISBN 9783110697803 / 3110697807.
- SOCR Home page: http://www.socr.umich.edu
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