BEGIN:VCALENDAR
PRODID:-//github.com/ical-org/ical.net//NONSGML ical.net 4.0//EN
VERSION:2.0
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:STANDARD
DTSTART:20241103T020000
RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11
TZNAME:EST
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20250309T020000
RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3
TZNAME:EDT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DESCRIPTION:About the Talk Join Maxwell Salvatore\, PhD\, MPH\, Postdoctor
 al Fellow at the University of Pennsylvania\, for a hands-on tutorial exp
 loring how to leverage the NIH All of Us Research Program data for biomed
 ical and public health research. Dr. Salvatore will demonstrate approache
 s for studying the risks\, benefits\, and pharmacogenomics of GLP-1 recep
 tor agonists (RAs) using electronic health records (EHR) and EHR-linked b
 iobank data. This session is ideal for researchers and students intereste
 d in learning how to navigate\, analyze\, and apply large-scale health da
 tasets in precision medicine and population health.About the Speaker Dr. 
 Maxwell Salvatore is a Postdoctoral Fellow working with Dr. Yong Chen in 
 the Department of Biostatistics\, Epidemiology\, and Informatics and Dr. 
 Marylyn Ritchie in the Department of Genetics at the University of Pennsy
 lvania. His work focuses on developing principled methods for analyzing e
 lectronic health record–linked biobanks and making these tools more acces
 sible to researchers. His research has spanned topics including COVID-19\
 , digestive cancers\, diabetes\, and obesity\, with an emphasis on precis
 ion medicine and health equity.\n\nAdmission:\nFree\n\nFood:\nSnacks\n\nD
 etails URL:\nhttps://medicine.yale.edu/event/lets-talk-data-nih-tutorial-
 nov-2025/\n
DTEND;TZID=America/New_York:20251121T110000
DTSTAMP:20260421T032942Z
DTSTART;TZID=America/New_York:20251121T093000
LOCATION:URL: https://yale.zoom.us/meeting/register/X_QmIRXnRyC72yk-XQFq3A
SEQUENCE:0
STATUS:Confirmed
SUMMARY:Let's Talk Data: How to use the NIH All of Us Tutorial
UID:831a4ce9-df3b-48d5-adfb-1bb7fec804db
END:VEVENT
END:VCALENDAR