SOCR Intro UMich 2018 - Revision history

Dinov: /* Examples of specific SOCR Resurces */

2018-04-23T15:39:18Z

‎Examples of specific SOCR Resurces

Dinov: /* SOCR Team */

2018-04-23T15:37:35Z

‎SOCR Team

Dinov at 15:36, 23 April 2018

2018-04-23T15:36:23Z

Dinov at 15:33, 23 April 2018

2018-04-23T15:33:24Z

Dinov: /* References */

2018-04-23T15:31:14Z

‎References

Dinov at 15:29, 23 April 2018

2018-04-23T15:29:44Z

Dinov at 15:18, 23 April 2018

2018-04-23T15:18:50Z

Dinov: Created page with "== SOCR News & Events: Introduction to the Statistics Online Computational Resource (SOCR) == ==Logistics== Image:SOCR_Logo_April_2018.png|150px|thumbnail|r..."

2018-04-23T15:04:16Z

Created page with "== SOCR News & Events: Introduction to the Statistics Online Computational Resource (SOCR) == ==Logistics== Image:SOCR_Logo_April_2018.png|150px|thumbnail|r..."

New page

== [[SOCR_News | SOCR News & Events]]: Introduction to the Statistics Online Computational Resource (SOCR) ==

==Logistics==
[[Image:SOCR_Logo_April_2018.png|150px|thumbnail|right| [http://socr.umich.edu SOCR Resource] ]]
* '''Event''': 2018 [http://nursing.umich.edu/academics/global-sexual-health-summer-institute Global Sexual Health Summer Institute]
* '''Series''': ''Big Data & Health Analytics''
* '''Session''': ''Big Healthcare Data: Research Challenges, AI Capabilities, and Educational Opportunities''
* '''Place/Time''': TBD
* '''Instructor''': [http://www.umich.edu/~dinov/ Ivo D Dinov]

==Abstract==
This session will focus on three Big Healthcare Data topics (1) healthcare challenges, (2) analytical capabilities, and (3) educational opportunities. Participants are encouraged to bring their laptops to experiment with some of the interactive content and hands-on demonstrations. JavaScript- and Java-enabled web-browsers would be useful. Participants interested in diving deeper into health analytics should also install [http://R-project.org R] and [http://www.rstudio.org/ RStudio graphical user interface]. The [http://myumi.ch/6xNgd unique URI for this session is http://myumi.ch/6xNgd] and it contains links to all resources that will be demonstrated.

== Desired learning outcomes==
* Understand the nature of Big Biomedical and Health data archives (challenges, strategies and pitfalls)
* Gain access to biomedical and health data, analytical protocols, software tools, and learning modules
* Experiment with some of the available software and computational services
* Compare and contrast advanced statistical concepts, grasp model assumptions/limitations and apply them for quantitative analyses in healthcare research.

== Coverage==
As time permits, we will cover some of the topics listed below.

===[http://www.socr.umich.edu/people/dinov/courses/DSPA_notes/00_Motivation.html Motivation]===
We will begin by examining several Big Biomedical case-studies (AD, PD, ALS). Then, we will try hands-on some complex visualization of neurodegenerative imaging, clinical and genetics data. The key point will be to identify the common characteristics of Big (Biomedical and Health) Data and define predictive analytics.

=== [http://www.socr.umich.edu/people/dinov/courses/DSPA_notes/05_DimensionalityReduction.html Simplifying Complex High-dimensional Data] ===
We will demonstrate examples of interrogating multisource, multidimensional and heterogeneous datasets.

=== Model-based vs. Model-free Analytical Methods ===
* [http://www.socr.umich.edu/people/dinov/courses/DSPA_notes/11_Apriory_AssocRuleLearning.html Association Rules Machine-Learning, Head and Neck Cancer Medications Case-Study]
* [http://www.socr.umich.edu/people/dinov/courses/DSPA_notes/12_kMeans_Clustering.html#4_case_study_1:_divorce_and_consequences_on_young_adults Divorce and Consequences on Young Adults Case-Study]
* [http://www.socr.umich.edu/people/dinov/courses/DSPA_notes/12_kMeans_Clustering.html#6_case_study_2:_pediatric_trauma Unsupervised Clustering, Pediatric Trauma Case-Study].

=== Learning Modules and Instructional Resources ===
* [http://wiki.socr.umich.edu/index.php/SOCR_Data Datasets] and [https://umich.instructure.com/courses/38100/files/folder/Case_Studies Case-Studies]
* [http://wiki.socr.umich.edu/index.php/SMHS Scientific Methods for Health Sciences EBook]
* [http://www.socr.umich.edu/people/dinov/courses.html Courses, including MOOCs]

=== [http://socr.umich.edu/HTML5/ SOCR Tools]===
The Statistics Online Computational Resource (SOCR) provides tools and services for capturing and interrogating biomedical and healthcare data. These include SOCR Analytical Toolkit (SOCRAT), SOCR Data Dashboard Webapp, SOCR PubMed Navigator, Motion Charts, Randomization, Resampling and Simulation Webapp
Violin Chart, Interactive (3D) Bivariate Normal Distribution Calculator webapp, Normal Distribution Calculator, Distributome Probability Calculators, Virtual Experiments, Simulators, Probability Distributome Navigator, Econometrics Webapps, XTK/HTML5 Brain Viewer and BrainBook Painter, DataSifter: Sharing and Obfuscation of Sensitive Data, CBDA: Compressive Big Data Analytics, 2D Interactive Voronoi Tessellation App, SOCR t-SNE Dimensionaltiy Reduction (TensorBoard) UKBB Machine Learning Modules, SOCR GitHub Resources, Apps, Code, Tools, and other Services.

==References==
* [http://wiki.socr.umich.edu/index.php/SOCR_News_2018_UMSN_SummerInstituteSession URL: http://wiki.socr.umich.edu/index.php/SOCR_News_2018_UMSN_SummerInstitute]
* Dinov, ID, 2018. [http://www.springer.com/us/book/9783319723464 Data Science and Predictive Analytics: Biomedical and Health Applications using R], Springer, Computer Science, ISBN 978-3-319-72346-4.
* [http://predictive.space Data Science and Predictive Analytics (DSPA) Website: http://predictive.space]
* [http://www.socr.umich.edu/people/dinov/publications.html Publications]

<hr>
* SOCR Home page: http://www.socr.umich.edu

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@@ Line 18: / Line 18: @@
-== Examples of specific SOCR Resurces ==
+== Examples of specific SOCR Resources ==
 * [http://socr.umich.edu/html/Navigators.html SOCR Navigators]
 * [[SOCR_Data | SOCR Datasets and Challenging Case-studies]]
@@ Line 30: / Line 30: @@
 The Statistics Online Computational Resource (SOCR) provides tools and services for capturing and interrogating biomedical and healthcare data. These include SOCR Analytical Toolkit (SOCRAT), SOCR Data Dashboard Webapp, SOCR PubMed Navigator, Motion Charts, Randomization, Resampling and Simulation Webapp
 Violin Chart, Interactive (3D) Bivariate Normal Distribution Calculator webapp, Normal Distribution Calculator, Distributome Probability Calculators, Virtual Experiments, Simulators, Probability Distributome Navigator, Econometrics Webapps, XTK/HTML5 Brain Viewer and BrainBook Painter, DataSifter: Sharing and Obfuscation of Sensitive Data, CBDA: Compressive Big Data Analytics, 2D Interactive Voronoi Tessellation App, SOCR t-SNE Dimensionaltiy Reduction (TensorBoard) UKBB Machine Learning Modules, SOCR GitHub Resources, Apps, Code, Tools, and other Services.
 == [http://socr.umich.edu/people/ SOCR Team] ==

@@ Line 32: / Line 32: @@
-== SOCR Team ==
+== [http://socr.umich.edu/people/ SOCR Team] ==
-[[Image:SOCR_MDP_April_2018_Pic2.png|500px|thumbnail|center| [http://socr.umich.edu SOCR] ]]
+[[Image:SOCR_MDP_April_2018_Pic2.png|600px|thumbnail|center| [http://socr.umich.edu/people SOCR Team] ]]
 ==References==

@@ Line 6: / Line 6: @@
 * '''Presenter''': [http://www.umich.edu/~dinov/ Ivo D Dinov]
-==Abstract==
+==Outline==
 [[Image:SOCR_Logo_April_2018.png|150px|thumbnail|right| [http://socr.umich.edu SOCR Resource] ]]
 The Statistics Online Computational Resource (SOCR) designs, validates and freely disseminates knowledge. SOCR provides portable online aids for probability, statistics, and health science education, promotes technology-enhanced instruction, supports efficient statistical computing, and advances predictive big data analytics. The SOCR infrastructure includes a repository of interactive applets, computational webapps, graphing tools, instructional resources, challenging case-studies, learning materials, and many curricular components.
@@ Line 22: / Line 22: @@
 * [[SOCR_Data | SOCR Datasets and Challenging Case-studies]]
 * [[SOCR_Books|Electronic Textbooks]]: [[EBook| Probability and Statistics EBook]], [[SMHS | Scientific Methods for Health Sciences]], [http://dspa.predictive.space Data Science and Predictive Analytics]
@@ Line 37: / Line 39: @@
 * Dinov, ID, 2018. [http://www.springer.com/us/book/9783319723464 Data Science and Predictive Analytics: Biomedical and Health Applications using R], Springer, Computer Science, ISBN 978-3-319-72346-4.
 * [http://predictive.space Data Science and Predictive Analytics (DSPA) Website: http://predictive.space]
 * [[SOCR_Intro_UMich_2018 | This summary, links and materials are available online: http://wiki.socr.umich.edu/index.php/SOCR_Intro_UMich_2018]].

← Older revision		Revision as of 15:31, 23 April 2018
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	* Dinov, ID, 2018. [http://www.springer.com/us/book/9783319723464 Data Science and Predictive Analytics: Biomedical and Health Applications using R], Springer, Computer Science, ISBN 978-3-319-72346-4.		* Dinov, ID, 2018. [http://www.springer.com/us/book/9783319723464 Data Science and Predictive Analytics: Biomedical and Health Applications using R], Springer, Computer Science, ISBN 978-3-319-72346-4.
	* [http://predictive.space Data Science and Predictive Analytics (DSPA) Website: http://predictive.space]		* [http://predictive.space Data Science and Predictive Analytics (DSPA) Website: http://predictive.space]
		+	* [[SOCR_Intro_UMich_2018 \| This summary, links and materials are available online: http://wiki.socr.umich.edu/index.php/SOCR_Intro_UMich_2018]].

@@ Line 2: / Line 2: @@
 ==Logistics==
 [[Image:SOCR_Logo_April_2018.png|150px|thumbnail|right| [http://socr.umich.edu SOCR Resource] ]]
-== Desired learning outcomes==
+== SOCR Services ==
-* Understand the nature of Big Biomedical and Health data archives (challenges, strategies and pitfalls)
+* Consultations on data analytic problems, computational challenges, statistical methods
-* Gain access to biomedical and health data, analytical protocols, software tools, and learning modules
+* Methodological support for research studies, grant applications, and publications,
-* Experiment with some of the available software and computational services
+* Technology support for data management, wrangling, visualization, and interrogation of complex, multi-source, heterogeneous biomedical and health data,
-* Compare and contrast advanced statistical concepts, grasp model assumptions/limitations and apply them for quantitative analyses in healthcare research.
+* High-performance, large-memory computing services, and
 == Coverage==
 As time permits, we will cover some of the topics listed below.
 === [http://socr.umich.edu/HTML5/ SOCR Tools]===