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DTSTART:20211107T020000
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UID:calendar.2116.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20220321T133123Z
DESCRIPTION:\nWhen and Where: \nMonday, April 04, 2022 3:30 pm to 4:30 pm
  \n Online \n\nSpeakers \nBhramar Mukherjee \n\nDescription: \nElectronic 
 Health Records linked with other auxiliary data sources hold tremendous po
 tential for conducting real time actionable research. However, one has to
  answer two fundamental questions before conducting inference: “Who is in 
 my study?” and “What is the target population of Inference?”. Without acco
 unting for selection bias one can quickly produce fast but inaccurate conc
 lusions. In this talk, I will discuss large-scale association studies acr
 oss multiple phenotypes, namely Phenome-wide association studies (PheWAS)
  that have gained traction in the genetics and medical informatics world. 
 I will present several applications of this tool in genetics, cancer and 
 for identifying risk factors for COVID-19 hospitalization and mortality. I
  will further discuss a statistical framework for jointly considering sele
 ction bias and phenotype misclassification in such analyses. This is joint
  work with Lars Fritsche, Lauren Beesley and Maxwell Salvatore and many o
 thers at the University of Michigan School of Public Health.Please join th
 e event.About Bhramar MukherjeeBhramar Mukherjee is John D. Kalbfleisch Co
 llegiate Professor and Chair, Department of Biostatistics; Professor, D
 epartment of Epidemiology, Professor, Global Public Health, University 
 of Michigan (UM) School of Public Health; Research Professor and Core Fac
 ulty Member, Michigan Institute of Data Science (MIDAS), University of M
 ichigan. She also serves as the Associate Director for Quantitative Data S
 ciences, University of Michigan Rogel Cancer Center. She is the Associate
  Workgroup Director for Cohort Development for U-M Precision Health, an i
 nstitution-wide presidential initiative. Her research interests include st
 atistical methods for analysis of electronic health records, studies of g
 ene-environment interaction, Bayesian methods, shrinkage estimation, an
 alysis of multiple pollutants. Collaborative areas are mainly in cancer, 
 cardiovascular diseases, reproductive health, exposure science and envir
 onmental epidemiology. She has co-authored more than 280 publications in s
 tatistics, biostatistics, medicine and public health and is serving as P
 I on NSF and NIH funded methodology grants. She is the founding director o
 f the University of Michigan’s summer institute on Big Data. Bhramar is a 
 fellow of the American Statistical Association and the American Associatio
 n for the Advancement of Science. She is the recipient of many awards for 
 her scholarship, service and teaching at the University of Michigan and b
 eyond. Bhramar and her team have been modeling the SARS-CoV-2 virus trajec
 tory in India for the last one year which has been covered by major media 
 outlets like Reuters, BBC, NPR, NYT, WSJ, Der Spiegel, Australian Na
 tional Radio and the Times of India. \n\nContact Information: \n CANSSI On
 tario \n\nCategories \n Data Science ARES \n\nAudiences \n FacultyGraduate
  Students
DTSTART;TZID=America/New_York:20220404T153000
DTEND;TZID=America/New_York:20220404T163000
LAST-MODIFIED:20220321T134315Z
SUMMARY:Using Electronic Health Records for Scientific Research: Promises a
 nd Perils
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/using-electronic-hea
 lth-records-scientific-research-promises-and-perils
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