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SUMMARY:The trajectories of complex disease - Professor Gil McVean (The El
 lison Institute of Technology\, Oxford)
DTSTART;VALUE=DATE-TIME:20241024T153000
DTEND;VALUE=DATE-TIME:20241024T163000
UID:https://new.talks.ox.ac.uk/talks/id/2079adab-7381-434a-8432-5d8d056c60
 12/
DESCRIPTION:The analysis of longitudinal data from electronic health recor
 ds (EHRs) has the potential to improve clinical diagnosis and enable perso
 nalised medicine\, motivating efforts to identify disease commonalities an
 d subtypes from patient comorbidity information and other modalities. We h
 ave developed an age-dependent topic-modelling (ATM) method that provides 
 a low-rank representation of longitudinal records of hundreds of distinct 
 diseases in large EHR datasets and applied it to c. 300\,000 individuals f
 rom UK Biobank and >200\,000 individuals from the All of Us program. A sur
 prisingly small number of disease trajectories capture known and novel com
 binations of disorders that occur throughout life and identify disease sub
 types that occur in multiple topics\, with differential genetic risk profi
 les. Such stratification improves understanding of patient risk and hetero
 geneity\, leading to better identification of genetic risk\, characterisat
 ion of pathological pathways and the discovery of new therapeutic targets.
 \nSpeakers:\nProfessor Gil McVean (The Ellison Institute of Technology\, O
 xford)
LOCATION:24-29 St Giles' (Large Lecture Theatre\, Department of Statistics
 )\, 24-29 St Giles' OX1 3LB
TZID:Europe/London
URL:https://new.talks.ox.ac.uk/talks/id/2079adab-7381-434a-8432-5d8d056c60
 12/
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DESCRIPTION:Talk:The trajectories of complex disease - Professor Gil McVea
 n (The Ellison Institute of Technology\, Oxford)
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