Difference between revisions of "Main Page"

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'''2019 Student Poster Presentations'''
 
'''2019 Student Poster Presentations'''
*[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496616682213 Data Mining Presentation]
+
*[https://drive.google.com/file/d/15Ej_jv9WCY-V-2ri6LeuKRwKvmQHe0AM/view?usp=sharing Data Mining Presentation]
*[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496590467731 Machine Learning Presentation]
+
*[https://drive.google.com/file/d/18hEPGSqKYvifqEKzizZpRWadfXK7y-rR/view?usp=sharing Machine Learning Presentation]
*[https://umich.app.box.com/s/xwc8ecl2l3gahlpdhobkm0zbx4dvu3qa/file/496560211380 Genomics Presentation]
+
*[https://drive.google.com/file/d/1cvssztV0MDeqJyiZOXH8PrszEj7Jm33-/view?usp=sharing Genomics Presentation]
 
'''2018 Student Poster Presentations'''
 
'''2018 Student Poster Presentations'''
 
*[https://drive.google.com/file/d/1TGNqkCAV9eBJ_-zHbiU-yo3N4Aowm_HB/view?usp=sharing Imaging Group Presentation]
 
*[https://drive.google.com/file/d/1TGNqkCAV9eBJ_-zHbiU-yo3N4Aowm_HB/view?usp=sharing Imaging Group Presentation]

Revision as of 19:18, 28 June 2021

Welcome to the U-M Big Data Summer Institute 2021 Wiki!

Electronic Health Records Group

Machine Learning Group

Imaging Group

Data Mining Group

Lectures

Week 1

  • Study Design and Inference, Observational Data and Bias, Parameter Estimation and Likelihood - Dr. Rod Little
    -Part 1, Part 1 Slides
    -Part 2, Part 2 Slides
    -Part 3, Part 3 Slides
    -Part 4, Part 4 Slides
    -Part 5, Part 5 Slides
  • Linear Algebra - Lap Sum Chan
    -Recording
    -Linear Algebra Slides
  • Linear Regression - Fatema Shafie Khorassani
    -Recording
    -Linear Regression Slides
  • Probability - Rupam Bhattacharyya
    -Recording
    -Probability Slides
  • Data Wrangling in R with dplyr - Dr. Matthew Flickinger
    -Lecture Slides
  • Data Visualization in R with ggplot2 - Dr. Matthew Flickinger
    -Lecture Slides

Week 2

  • Machine Learning - Dr. Jenna Wiens
  • Data Mining - Jiong Zhu
  • Logistic Regression - Aubrey Annis
    -Recording
    -Logistic Regression Slides
  • Generalized Linear Models - Aubrey Annis
    -Recording
    -GLM Slides
  • R Markdown - Dr. Phil Boonstra
    -Synchronous Lecture Recording
    -R Markdown Slides
  • Python - Dr. Fred Feng
    -Synchronous Lecture Part I and II Recording
    -Synchronous Lecture Part III and IV Recording


Week 3

  • Assessment of Predictive Models - Dr. Phil Boonstra
    -Recording
  • Causal Inference - Dr. Walter Dempsey
    -Recording
    -Causal Inference Slides
  • Model Selection - Nicky Wakim
    -Recording
    -AUC/ROC Recording
    -Model Selection Slides
    -Annotated Model Selection Slides
  • Data Visualization Workshop
    -Synchronous Lecture Recording
    -Data Visualization Slides

Week 4

  • Introduction to Bayes - Dr. Xiaoquan William Wen
  • Missing Data - Dr. Peisong Han
  • Clustering - Fahad Kamran

Week 5

  • Social Networks - Dr. Eytan Adar
  • Electronic Health Records - Dr. Xu Shi
  • Genetics/Genomics - Dr. Jean Morrison
  • Health Disparities in Strokes - Dr. Lynda Lisabeth
  • Precision Health - Dr. Sachin Kheterpal

Week 6

  • Data Integration and Precision Medicine - Dr. Veera Baladandayuthapani
  • Radiation Oncology - Dr. Arvind Rao
  • Better, Not Just Bigger Data Analytics - Dr. Brahmajee Nallamothu
  • Clinical Trials - Dr. Kelley Kidwell

Week 7

  • Preparing for Graduate School - Dr. Kelley Kidwell
  • CVs and Resumes - Krystle Forbes
  • Scientific Writing - Dr. Brett Griffiths
  • Pick Me! - Dr. Brett Griffiths

Week 8

Journey Lectures

Past BDSI Student Poster Presentations

2019 Student Poster Presentations

2018 Student Poster Presentations

2017 Student Poster Presentations

2017 Symposium Lecturers

Additional Resources