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UID:20251104T070854EST-6086iOI0V8@132.216.98.100
DTSTAMP:20251104T120854Z
DESCRIPTION:Efficient Use of EHR for Biomedical Translational Research\n\nT
 ianxi Cai is a professor of Biostatistics at Harvard T.H. Chan school of p
 ublic health and a professor of Biomedical Informatics at Harvard Medical 
 School. She received her Doctoral degree from Harvard in 1999 and taught a
 t the University of Washington for two years before returning to Harvard a
 s a faculty. Tianxi’s current research focuses mainly in the areas of risk
  prediction and personalized medicine with biomarkers and genomic studies\
 ; statistical and machine learning\, analysis of EHR data. For more info p
 lease visit: https://www.hsph.harvard.edu/tianxi-cai/\n\n	While clinical tr
 ials remain a critical source for studying disease risk\, progression and 
 treatment response\, they have limitations including the generalizability 
 of the study findings to the real world and the limited ability to test br
 oader hypotheses. In recent years\, due to the increasing adoption of elec
 tronic health records (EHR) and the linkage of EHR with specimen bio-repos
 itories\, large integrated EHR datasets now exist as a new source for tran
 slational research. These datasets open new opportunities for deriving rea
 l-word\, data-driven prediction models of disease risk and progression as 
 well as unbiased investigation of shared genetic etiology of multiple phen
 otypes. Yet\, they also bring methodological challenges. For example\, obt
 aining validated phenotype information\, such as presence of a disease con
 dition and treatment response\, is a major bottleneck in EHR research\, as
  it requires laborious medical record review. A valuable type of EHR data 
 is narrative free-text data. Extracting accurate yet concise information f
 rom the narrative data via natural language processing is also challenging
 . In this talk\, I’ll discuss various statistical and informatics methods 
 that illustrate both opportunities and challenges. These methods will be i
 llustrated using EHR data from Partner’s Healthcare.\n\n\n\n
DTSTART:20180320T193000Z
DTEND:20180320T203000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Tianxi Cai\, ScD\, Harvard T.H. Chan - School of Public Health
URL:/mathstat/channels/event/tianxi-cai-scd-harvard-th
 -chan-school-public-health-285891
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