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Discovering Medical Information from User-Generated Content

31 Oct
Wednesday, 10/31/2012 7:00am to 8:00am

Elad Yom-Tov
Microsoft Research

Computer Science Building, Room 151

Faculty Host: James Allan


Collecting medical information from large cohorts is expensive and is frequently biased by the difficulty people experience in reporting effects which have late onset, are due to several confounding effects, or are related to sensitive subjects. In this talk, I will show that specific types of User Generated Content (UGC) are less influenced by such biases, and are thus a low-cost alternative for extracting medical information from very large populations. I will demonstrate our approach to learning from UGC using examples from post-market drug surveillance, understanding childhood obesity and its effect on social and physical wellbeing, the stages of information seeking by cancer patients, and the detrimental results of good intention on anorexia patients.


Elad Yom-Tov is a Senior Researcher at Microsoft Research. Before joining Microsoft he was with Yahoo Research, IBM Research, and Rafael. Dr. Yom-Tov studied at Tel-Aviv University and the Technion, Israel. He has published two books, over 60 papers (of which 3 were awarded prizes), and filed more than 30 patents (13 of which have been granted so far). His primary research interests are in large-scale Machine Learning, Information Retrieval, and Social Analysis. The results of his work have flown at four times the speed of sound, enabled people to communicate with computers using only their brain-waves, and analyzed the cellphone records of a significant portion of the worlds' population. He is a Senior Member of IEEE and held the title of Master Inventor while at IBM.