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	<title>SOCR News NIH BRAIN 2020 - Revision history</title>
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	<updated>2026-07-22T01:14:08Z</updated>
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		<id>https://wiki.socr.umich.edu/index.php?title=SOCR_News_NIH_BRAIN_2020&amp;diff=17049&amp;oldid=prev</id>
		<title>Dinov: Created page with &quot;==  SOCR News &amp; Events: 2020 6th annual BRAIN Initiative Investigators Virtual Meeting: Spacekime Analytics==   ==Logistics== Image:SOCR_UMich_2020a.png|150px...&quot;</title>
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		<updated>2020-05-28T18:14:49Z</updated>

		<summary type="html">&lt;p&gt;Created page with &amp;quot;== &lt;a href=&quot;/index.php/SOCR_News&quot; title=&quot;SOCR News&quot;&gt; SOCR News &amp;amp; Events&lt;/a&gt;: 2020 6th annual BRAIN Initiative Investigators Virtual Meeting: Spacekime Analytics==   ==Logistics== Image:SOCR_UMich_2020a.png|150px...&amp;quot;&lt;/p&gt;
&lt;p&gt;&lt;b&gt;New page&lt;/b&gt;&lt;/p&gt;&lt;div&gt;== [[SOCR_News | SOCR News &amp;amp; Events]]: 2020 6th annual BRAIN Initiative Investigators Virtual Meeting: Spacekime Analytics==&lt;br /&gt;
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==Logistics==&lt;br /&gt;
[[Image:SOCR_UMich_2020a.png|150px|thumbnail|right| [http://socr.umich.edu SOCR Resource] ]]&lt;br /&gt;
* '''Event''': [https://www.labroots.com/ms/virtual-event/2020-6th-annual-brain-initiative-investigators-virtual-meeting 2020 6th annual BRAIN Initiative Investigators Virtual Meeting]&lt;br /&gt;
* '''Date/Time''': Monday-Tuesday, June 1-2, 2020, Virtual Meeting&lt;br /&gt;
* '''Registration''': [https://events.labroots.com/event/BRAIN-Initiative-Investigators-Virtual-Meeting/ Registration]&lt;br /&gt;
* '''Webcast''': [https://events.labroots.com/event/BRAIN-Initiative-Investigators-Virtual-Meeting/ Webcast]&lt;br /&gt;
* '''Poster''': [https://events.labroots.com/event/BRAIN-Initiative-Investigators-Virtual-Meeting/en-us#!/Poster_Hall/n438411/ Poster PDF (requires registration)]&lt;br /&gt;
* '''Title''':  ''Data Science, Time Complexity, and Spacekime Analytics''&lt;br /&gt;
* '''Presenter''':  [http://umich.edu/~dinov Ivo Dinov]&lt;br /&gt;
* '''PDF''': [https://socr.umich.edu/docs/uploads/2020/NIH_BRAIN_Spacekime_Poster_TDA14.pdf Poster]&lt;br /&gt;
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== Abstract==&lt;br /&gt;
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The immersion of Big Data in all human experiences presents important challenges of managing, modeling, analyzing, interpreting, and visualizing complex information. There is a substantial need to develop, validate, productize, and support novel mathematical techniques, advanced statistical computing algorithms, transdisciplinary tools, and effective artificial intelligence apps. &lt;br /&gt;
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Spacekime analytics is a new technique for modeling high-dimensional longitudinal data. This approach relies on extending the notions of time, events, particles, and wavefunctions to complex-time (kime), complex-events (kevents), data and inference-functions. We will illustrate how the kime-magnitude (longitudinal time order) and kime-direction (phase) affect the subsequent predictive analytics and the induced scientific inference. The mathematical foundation of spacekime calculus will reveal various statistical implications including inferential uncertainty and a Bayesian formulation of spacekime analytics. Complexifying time allows the lifting of all commonly observed processes from the classical 4D Minkowski spacetime to a 5D spacetime manifold, where a number of interesting mathematical problems arise. &lt;br /&gt;
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Direct data science applications of spacekime analytics will be demonstrated using simulated data, clinical observations (e.g., UK Biobank), and environmental air quality data.&lt;br /&gt;
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* Joint work with Milen V. Velev (Burgas University, Bulgaria).&lt;br /&gt;
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==Demos==&lt;br /&gt;
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* [https://www.socr.umich.edu/spacekime/ Spacekime website]&lt;br /&gt;
* [http://tciu.predictive.space/ Time-Complexity and Inferential Uncertainty (TCIU)]&lt;br /&gt;
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==References==&lt;br /&gt;
* This work is sponsored in part by NIH Grants [http://projectreporter.nih.gov/project_info_details.cfm?aid=8975330&amp;amp;icde=25689118 P30 DK089503], [http://projectreporter.nih.gov/project_info_description.cfm?aid=8821268&amp;amp;icde=22205726 P20 NR015331], [https://projectreporter.nih.gov/project_info_description.cfm?aid=9816658 R01CA233487], and [https://projectreporter.nih.gov/project_info_details.cfm?aid=9842024 R01MH121079], as well as, NSF Grants [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1916425 1916425], [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1734853 1734853] and [http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1636840 1636840].&lt;br /&gt;
* Dinov, ID and Velev, MV (2021) [https://www.degruyter.com/view/title/576646 Data Science: Time Complexity, Inferential Uncertainty, and Spacekime Analytics], De Gruyter (STEM Series), Berlin/Boston, ISBN 9783110697803 / 3110697807. &lt;br /&gt;
* SOCR Home page: http://www.socr.umich.edu&lt;br /&gt;
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==See also==&lt;br /&gt;
* [http://socr.umich.edu/HTML5/ General SOCR Webapps]&lt;br /&gt;
* [http://socr.umich.edu/HTML5/BrainViewer/ SOCR BrainViewer]&lt;br /&gt;
* [https://socr.umich.edu/HTML5/MotionChart/ Motion Charts webapp] (try it with your own high-dimensional longitudinal data, e.g., [https://wiki.socr.umich.edu/index.php/SOCR_Data_121608_OzoneData Ozone Data])&lt;br /&gt;
* [http://socr.umich.edu/HTML5/SOCR_TensorBoard_UKBB/ Hands-on interactive visualization of extremely high-dimensional data (learning module and webapp)]&lt;br /&gt;
** [http://socr.umich.edu/HTML5/SOCR_TensorBoard_UKBB/UsersData.html Country Ranking study]&lt;br /&gt;
** [http://socr.umich.edu/CSCD/html/Cores/Macore2/CSCD_SOCR_Diabetes_CaseStudy/ Diabetes Case-Study]&lt;br /&gt;
* [http://myumi.ch/O49zG Predicting Hospitalization-based Pressure Injuries (webapp)]&lt;br /&gt;
* [http://myumi.ch/qgY7v Virtual Hospital and Simulated Patient EHR Data (webapp)]&lt;br /&gt;
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		<author><name>Dinov</name></author>
		
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