Difference between revisions of "Main Page"
Jump to navigation
Jump to search
| Line 13: | Line 13: | ||
=== Week 1 === | === Week 1 === | ||
*Study Design and Inference, Observational Data and Bias, Parameter Estimation and Likelihood - Dr. Rod Little | *Study Design and Inference, Observational Data and Bias, Parameter Estimation and Likelihood - Dr. Rod Little | ||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
*Linear Algebra - Lap Sum Chan | *Linear Algebra - Lap Sum Chan | ||
-[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=7806d705-2514-46f1-b81f-ad400031332d Recording] | -[https://sph.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=7806d705-2514-46f1-b81f-ad400031332d Recording] | ||
Revision as of 09:58, 7 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
- Linear Algebra - Lap Sum Chan
-Recording
- Linear Regression - Fatema Shafie Khorassani
-Recording
- Probability - Rupam Bhattacharyya
-Recording
- 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 Lecturers
- 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
