Difference between revisions of "Main Page"
Jump to navigation
Jump to search
Line 25: | Line 25: | ||
=== Week 2 === | === Week 2 === | ||
+ | *Machine Learning - Dr. Jenna Wiens | ||
+ | *Logistic Regression - Aubrey Annis | ||
+ | *Generalized Linear Models - Aubrey Annis | ||
+ | *R Markdown - Dr. Phil Boonstra | ||
+ | *Python - Dr. Fred Feng | ||
=== Week 3 === | === Week 3 === | ||
+ | *Assessment of Predictive Models - Dr. Phil Boonstra | ||
+ | *Causal Inference - Dr. Walter Dempsey | ||
+ | *Model Selection - Nicky Wakim | ||
=== Week 4 === | === Week 4 === | ||
+ | *Introduction to Bayes - Dr. Xiaoquan William Wen | ||
+ | *Missing Data - Dr. Peisong Han | ||
+ | *Clustering - Fahad Kamran | ||
=== Week 5 === | === 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 === | === 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 === | === 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 === | === Week 8 === |
Revision as of 20:12, 6 June 2021
Welcome to the U-M Big Data Summer Institute 2021 Wiki!
Contents
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 2 -Part 3 -Part 4 -Part 5
- Linear Algebra - Lap Sum Chan
- Linear Regression - Fatema Shafie Khorassani
- Probability - Rupam Bhattacharyya
- Data Wrangling in R with dplyr - Dr. Matthew Flickinger
- Data Visualization in R with ggplot2 - Dr. Matthew Flickinger
Week 2
- Machine Learning - Dr. Jenna Wiens
- Logistic Regression - Aubrey Annis
- Generalized Linear Models - Aubrey Annis
- R Markdown - Dr. Phil Boonstra
- Python - Dr. Fred Feng
Week 3
- Assessment of Predictive Models - Dr. Phil Boonstra
- Causal Inference - Dr. Walter Dempsey
- Model Selection - Nicky Wakim
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
Past BDSI Student Poster Presentations
2019 Student Poster Presentations
2018 Student Poster Presentations
- Imaging Group Presentation
- Machine Learning Group Presentation
- Genetics Group Presentation
- Data Mining Presentation
2017 Student Poster Presentations
2017 Symposium Reference Files
2017 Symposium Projects
- A Time-to-Event Analysis of Heart Failure via Electronic Health Records
- Melanoma Detection by Classifying Skin Lesion Images
- Classifying Skin Lesions Images Using Adaptive Boosting
- Machine Learning Classification of Skin Lesion Images
- Genomics: Genome Storage and Assembly
- Predicting the Transcriptome from the Genome
- Classification of Cell Types from Peripheral Mononuclear Blood Cells
- EHR-Based Study of Long-Term Infectious Diseases
- Visualizing Lab and Phenotype Associations Using PheWAS and Electronic Health Records
- Data Mining: Microenvironment Microarray Spot Based Approach for Cell Prediction
- Estimating Cell Growth with Machine Learning and Data Mining
Additional Resources
- Daily Schedule
- Social Events Schedule TBD