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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 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
- 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
-Recording -Social Network Slides
- Electronic Health Records - Dr. Xu Shi
- Genetics/Genomics - Dr. Jean Morrison
-Recording -Genetics/Genomics Slides
- Precision Health - Dr. Sachin Kheterpal
-Recording
Week 6
- Data Integration and Precision Medicine - Dr. Veera Baladandayuthapani
-Recording -Bayesian Precision Medicine Slides
- Health Disparities in Strokes - Dr. Lynda Lisabeth
-Recording -Stroke Disparities Slides
- Radiation Oncology - Dr. Arvind Rao
-Recording -Radiation Oncology Slides
- Better, Not Just Bigger Data Analytics - Dr. Brahmajee Nallamothu
- Scientific Writing - Dr. Brett Griffiths
- Pick Me! - Dr. Brett Griffiths
Week 7
- Clinical Trials - Dr. Kelley Kidwell
-Recording -Clinical Trials Slides
- Microaggressions Workshop - Dr. Yatesha Robinson
-Recording -Microaggressions Slides
- Preparing for Graduate School - Dr. Kelley Kidwell
-Recording -Preparing for Graduate School Slides
- CVs and Resumes - Krystle Forbes
-Recording -CVs and Resumes Slides
Symposium
2021 Student Poster Presentations
Journey Lectures
- Week 1: Dr. Michael Boehnke
- Week 2: Dr. Mousumi Banerjee
- Week 3: Dr. Lauren Beesley VanDervort
- Week 4: Dr. Rod Little
- Week 5: Dr. Sharon Kardia
- Week 6: Dr. Dubois Bowman
- Week 7: Dr. Jeremy Taylor
- Week 8: Dr. Bhramar Mukherjee
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
2019 Symposium Group Posters
- Evaluating the Uncertainty of Anti-Cancer Drug Classification Models
- Polygenic Risk for Hypertension through the Lens of Population Genetics
- Quantitative Analysis of Polygenic Risk Score Prediction in the Genes for Good Cohort
- Exploring the Robustness of Deep Learning Architectures
- Survival Analysis of Glioblastoma Patients Through Tumor Tissue Deconvolution
- Examining the Effects of Cancer Cell Line Genetics on Drug Efficacy
- Predicting Efficacy of Chemotherapies for Diverse Primary Tumors Using Cell Line Genetics and Tissue Type
2017 Symposium Group Posters
- 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
