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DTSTAMP:20250804T161121Z
DESCRIPTION:Farhad Shokoohi\, PhD\n\nPostdoctoral Fellow\, Department of Ma
 thematics and Statistics\, 51�Թ���\n\nFeature selection in high-
 dimensional heterogeneous time-to-event data\; A study on Ovarian Cancer\n
 \nALL ARE WELCOME\n\nAbstract:\n\nOvarian cancer is among the leading caus
 es of cancer deaths and extremely difficult to detect at early stages. DNA m
 ethylation profile of a genome may provide valuable infor­mation\, and may 
 even be part of a genetic signature for survival time after the surgery. I
 t is therefore of interest to study how time to the recurrence of ovarian 
 cancer is related to methylation levels of gene promoters. A recent study 
 on relationship between genes and time to the recurrence of ovarian cancer
  after surgery has been carried out and the methylations of a large number
  of genes have been measured. The observations are subject to right censor
 ing and indicate some signs of heterogeneity. To take this latter feature 
 into account in our analysis\, we consider a finite mixture of accelerated 
 failure time models. Since a large number of genes measured in the study\,
  we apply screening and penalization methods to identify genes that can ha
 ve considerable effect on survival after the surgery. There are many method
 s for dealing with time-to-event data with large number of features (p) an
 d small sample size (n). There is\, however\, no method in the current lit
 erature for analyzing censored data with substructure in large p - small n
  setting. In this talk\, we consider variable selection in finite mixture m
 odels when observations are subject to right censoring. We propose a penal
 ized likelihood method for this problem. Large sample prop­erties of the p
 roposed method are studied. Simulation studies are carried out to evaluate
  the performance of the proposed method. The ovarian cancer data are analy
 zed and the results of the study is discussed.\n\nkeywords: Accelerated Fa
 ilure Time\, DNA Methylation\, EM Algorithm\, Feature Selection\, Finite M
 ixture Model\, Ovarian Cancer\, Right Censoring.\n\nThis is a joint work w
 ith professor Masoud Asgharian\, professor Abbas Khalili (51�Թ���Universit
 y)\, and professor Shili Lin (The Ohio State University).\n\nBio:\n\nwww.m
 ath.mcgill.ca/farhad/\n\n \n\n \n\n \n
DTSTART:20160308T203000Z
DTEND:20160308T213000Z
LOCATION:Room 24\, Purvis Hall\, CA\, QC\, Montreal\, H3A 1A2\, 1020 avenue
  des Pins Ouest
SUMMARY:Biostatistics Seminar - 'Feature selection in high-dimensional hete
 rogeneous time-to-event data\; A study on Ovarian Cancer'
URL:/epi-biostat-occh/channels/event/biostatistics-sem
 inar-feature-selection-high-dimensional-heterogeneous-time-event-data-stud
 y-ovarian-258127
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