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SUMMARY:Virtual BSU Seminar: “Methodological Advances in Risk Prediction
 " - Dr Glen Martin\, University of Manchester
DTSTART:20211022T130000Z
DTEND:20211022T140000Z
UID:TALK163891@talks.cam.ac.uk
CONTACT:Alison Quenault
DESCRIPTION:Risk prediction models are tools that compute the risk of an a
 dverse outcome given a set of patient characteristics. Arising from the de
 sire to move health systems away from managing or curing disease towards p
 reventative medicine\, these tools have become popular and several are now
  embedded in clinical practice. They are typically based on statistical or
  machine learning models\, derived by analyzing historical patient data (e
 .g.\, routinely collected electronic health records). Our group is engaged
  in a program of methodological research to improve the ways in which thes
 e models are developed and validated. In this talk\, I will overview some 
 of this methodological work\, including topics such as: (i) updating of ex
 isting risk prediction models to suit local settings\, (ii) missing data/ 
 informative presence\, (iii) incorporating longitudinal data in risk predi
 ction models\, (iv) penalisation and shrinkage for prediction models\, and
  (v) development of models for multiple outcomes (multivariate prediction 
 models).  
LOCATION:Virtual Seminar 
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