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UID:267@dds.technion.ac.il

DTSTART;TZID=Asia/Jerusalem:20221113T130000

DTEND;TZID=Asia/Jerusalem:20221113T133000

DTSTAMP:20221106T081954Z

URL:https://dds.technion.ac.il/iemevents/adverse-reactions-can-we-find-the
 -effects-from-social-media/

SUMMARY:Assessing causal effects of medical interventions from social media
 : The contribution of different algorithmic approaches [	\n					Graduate S
 tudent Seminar\n					Seminars\n			\n	]
DESCRIPTION:By: M.Sc.  Yael Kiselman\n Advisors: Dr. Elad Yom-Tov\n Where: 
 Bloomfield 527 From:\nTechnion\nAbstract: The gold-standard approach to es
 tablishing causality is through a randomized controlled trial (RCT) where 
 participants are randomly assigned to either a treatment or a control grou
 p. Unfortunately\, in many cases only observational data (e.g.\, social me
 dia) is available\, but these data include potential sources of bias. Seve
 ral methods have been proposed to mitigate the effect of such biases\, for
  example\, the Self Controlled Case Series method. In our work we compare 
 three approaches for causal discovery and apply them to social media data 
 (specifically\, Reddit) to identify side effects of medical interventions.
  Our results show that all examined methods replicate known findings from 
 the literature\, except for cases where sample sizes are insufficient. Thu
 s\, our work demonstrates the usefulness of social media data\, analyzed b
 y appropriate algorithmic approaches\, to facilitate the discovery of adve
 rse reactions of medical interventions through real-world data.
CATEGORIES:Graduate Student Seminar,Seminars
LOCATION:Bloomfield 527

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DTSTART:20221030T010000

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