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=== Week 6 === | === Week 6 === | ||
*Data Integration and Precision Medicine - Dr. Veera Baladandayuthapani | *Data Integration and Precision Medicine - Dr. Veera Baladandayuthapani | ||
+ | -[https://umich.zoom.us/rec/share/kAaCkeWE-AcmqQ3A8wSEYmTLh16Ac5n5EZ84g_LJCq8FxFMrqdkP3MFUm8zNbmzI.xu70bqdFerecQ8wF Recording] | ||
+ | -[https://umich.zoom.us/rec/share/LmCFefGUAulqT50i0hoVO74Btjqp6e5ypUTm-spUY5MGqDJjD7vaaZCkapVwCCF8.iA2SDdyVancAGK-I Bayesian Precision Medicine Slides] | ||
*Health Disparities in Strokes - Dr. Lynda Lisabeth | *Health Disparities in Strokes - Dr. Lynda Lisabeth | ||
+ | -[https://umich.zoom.us/rec/share/RQ9vlCzxoWEE6hpvLPz-vanDd0gO6ujGyzM7_aDDUO6dcP_pZOi6B1ARfXBiVlHj.GmmaIIbUAmu8--MG Recording] | ||
+ | -[https://drive.google.com/file/d/1XbynY5LgEvVXZxuhOr-XHg-czxCbTvA6/view?usp=sharing Stroke Disparities Slides] | ||
*Radiation Oncology - Dr. Arvind Rao | *Radiation Oncology - Dr. Arvind Rao | ||
+ | -[https://umich.zoom.us/rec/share/Wwjj54gusawthzmdsDGSh2PQePUjiEpbxj0vE70BB3s23ctn_aJMXKiFUB6gO-tC.VC9J-kyESKs2iqv7 Recording] | ||
+ | -[https://drive.google.com/file/d/1Qkdy9lAsL6ckm1ozfKLozuGUdvYnmXcT/view?usp=sharing Radiation Oncology Slides] | ||
*Better, Not Just Bigger Data Analytics - Dr. Brahmajee Nallamothu | *Better, Not Just Bigger Data Analytics - Dr. Brahmajee Nallamothu | ||
*Scientific Writing - Dr. Brett Griffiths | *Scientific Writing - Dr. Brett Griffiths | ||
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=== Week 7 === | === Week 7 === | ||
*Clinical Trials - Dr. Kelley Kidwell | *Clinical Trials - Dr. Kelley Kidwell | ||
+ | -[https://umich.zoom.us/rec/share/GncgIvaaxWDEawBcYej-WYujm4jvNuuOANEiAyHxcMsl9n972qfCxZiaoYIwzdj1.oR855M-YO3bTFmYC Recording] | ||
+ | -[https://drive.google.com/file/d/10srF-xs2i8hMzEaZ2ypobtNinBuFqGtc/view?usp=sharing Clinical Trials Slides] | ||
+ | *Microaggressions Workshop - Dr. Yatesha Robinson | ||
+ | -[https://umich.zoom.us/rec/share/WlLorXoVboO17DIS8XULt6NuNDMWoMwQJJ1PsvslE-esY3_0OfsgSZrSr-r9xEQo.8Yjj8C5xKE8OYvtY Recording] | ||
+ | -[https://drive.google.com/file/d/1ZmqU4Nmyb1xWA6q9KzkXRaOANlWCZdzt/view?usp=sharing Microaggressions Slides] | ||
*Preparing for Graduate School - Dr. Kelley Kidwell | *Preparing for Graduate School - Dr. Kelley Kidwell | ||
+ | -[https://umich.zoom.us/rec/share/lk9I9X8CG_XuaLADcKHoNwI6XJb7Iwc52RYEdF45tuyN4UzG7c124bRbsPCdED4D.n8vOye3bFJ2rtSth Recording] | ||
+ | -[https://drive.google.com/file/d/1YAMvCna7XQJ4gtEGbGz_CzvwPZEgU84E/view?usp=sharing Preparing for Graduate School Slides] | ||
*CVs and Resumes - Krystle Forbes | *CVs and Resumes - Krystle Forbes | ||
+ | -[https://umich.zoom.us/rec/share/VxOTekAs_-lHEqmmBcXfKHnffXtJmEkaeBxCuHMyvdmgYD_23fBfvRxM6SLx1ps.JJ9-oTpocEGCk5GV Recording] | ||
+ | -[https://drive.google.com/file/d/1CvDy3bf9gNXQyshbe4dpuBDS_3Uxu0Uy/view?usp=sharing CVs and Resumes Slides] | ||
− | === | + | === Symposium === |
+ | '''2021 Student Poster Presentations''' | ||
+ | *[https://drive.google.com/file/d/13jnaIPDLKqA2U8pyHcZv05Z78N-vlXQb/view?usp=sharing Data Mining] | ||
+ | *[https://drive.google.com/file/d/1BnJBplTRmJ0A2dsrVx6d6hmi25-sIldG/view?usp=sharing Machine Learning] | ||
+ | *[https://drive.google.com/file/d/1WERrG7d9MmVRMGifXZLbVkpQXFAFkhPV/view?usp=sharing Imaging] | ||
+ | *[https://drive.google.com/file/d/1SUnjN-02JcpnJ-nU2g8OGcT5Wl81qece/view?usp=sharing Electronic Health Records] | ||
== Journey Lectures == | == Journey Lectures == | ||
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*Week 5: Dr. Sharon Kardia | *Week 5: Dr. Sharon Kardia | ||
*Week 6: Dr. Dubois Bowman | *Week 6: Dr. Dubois Bowman | ||
− | *Week 7: Dr. Jeremy Taylor | + | *[https://umich.zoom.us/rec/share/t-VrNSdpNAXHPEnspphj44Mk2ATT6P3SXGJcfKlQmabjjMLDcI-9Zry9_XI-hYcG.iUYlDFQe4qS9SpTj Week 7: Dr. Jeremy Taylor] |
*Week 8: Dr. Bhramar Mukherjee | *Week 8: Dr. Bhramar Mukherjee | ||
Latest revision as of 11:44, 30 July 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 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