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DTSTAMP:20250507T092448Z
DESCRIPTION:'Developing machine learning models for phenotype prediction vs
  disease mechanism detection. A play in 3 acts.'\n\nAnna Goldenberg (Unive
 rsity of Toronto)\n	Tuesday December 4\, 12-1pm\n	McIntyre Building\, Room 1
 027\n	\n	Abstract: There is a great potential for machine learning to contri
 bute to understanding complex human diseases and clinical decision making.
  Rapidly evolving biotechnologies are making it progressively easier to co
 llect multiple and diverse genome-scale datasets to address clinical and b
 iological questions. Much of the work is driven by a great human propensit
 y to explain the unknown. We have to be careful\, however\, in trying to e
 xplain models applied to biological data that were built for purposes othe
 r than data explanation\, such as models that were built purely to predict
  a specific phenotype. In this talk\, if time allows\, I will talk about 3
  different applications. The first model predicts whether a child with a T
 P53 mutation is likely to get cancer before the age of 6 using regularized
  regression\; the second model predicts drug response using variational au
 toencoders\; the third is a graphical model that was built specifically to
  identify disease mechanisms. In each case\, I will highlight our attempts
  to explain the biology behind the predictions and the perils of doing so.
 \n
DTSTART:20181204T170000Z
DTEND:20181204T180000Z
LOCATION:Room 1027\, McIntyre Medical Building\, CA\, QC\, Montreal\, H3G 1
 Y6\, 3655 promenade Sir William Osler
SUMMARY:Seminar Series in Quantitative Life Sciences and Medicine
URL:/qls/channels/event/seminar-series-quantitative-li
 fe-sciences-and-medicine-292040
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