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*Clustering - Fahad Kamran
 
*Clustering - Fahad Kamran
 
     -[https://umich.zoom.us/rec/share/_WwhjJCULyM_MkP4bYXY19neSFsQNKZJdUd1iW6KF3_x3mYvTkwAKZTyDuFGb7Of.m-XMCko8ENNkOLzR Clustering I Recording]
 
     -[https://umich.zoom.us/rec/share/_WwhjJCULyM_MkP4bYXY19neSFsQNKZJdUd1iW6KF3_x3mYvTkwAKZTyDuFGb7Of.m-XMCko8ENNkOLzR Clustering I Recording]
     -Clustering II Recording
+
     -[https://umich.zoom.us/rec/share/5bJdAvSc8cBYvfmuSQvUjIFRTeEJm4TgzXtc1YDEWxhZRbn_5fBLQRQEc2XD2s-i.-CAq2U5r0qhesbxa Clustering II Recording]
 
     -[https://drive.google.com/file/d/1ZIOMkz8Q1rg7OHElHvZVbvc-L1LWwYR_/view?usp=sharing Clustering I Slides]
 
     -[https://drive.google.com/file/d/1ZIOMkz8Q1rg7OHElHvZVbvc-L1LWwYR_/view?usp=sharing Clustering I Slides]
 
     -[https://drive.google.com/file/d/1VTuyzt6KAt1IcXjVMIMVQmiqGv1dlbTa/view?usp=sharing Clustering II Slides]
 
     -[https://drive.google.com/file/d/1VTuyzt6KAt1IcXjVMIMVQmiqGv1dlbTa/view?usp=sharing Clustering II Slides]

Revision as of 16:24, 29 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
    -Intro to Bayes I Recording
    -Intro to Bayes II Recording
    -Intro to Bayes I Slides
    -Intro to Bayes II Slides
  • Missing Data - Dr. Peisong Han
  • Clustering - Fahad Kamran
    -Clustering I Recording
    -Clustering II Recording
    -Clustering I Slides
    -Clustering II Slides

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