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VERSION:2.0
CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20220325T103302Z
DTSTART:20220405T100000Z
DTEND:20220405T110000Z
SUMMARY:Seminar: Dr Ali Hassaine - Untangling the complexity of multimorb
 idity with machine learning
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}k1h2-l16ac0
 ju-coav88
DESCRIPTION:The prevalence of multimorbidity has been increasing in recen
 t years\, posing a major burden for health care delivery and service. Un
 derstanding its determinants and impact is proving to be a challenge yet
  it offers new opportunities for research to go beyond the study of dise
 ases in isolation. In this talk\, we cover some promising machine learni
 ng techniques such as matrix factorisation\, deep learning\, and topolog
 ical data analysis and how these can take multimorbidity research beyond
  cross-sectional\, expert-driven or confirmatory approaches to gain a be
 tter understanding of evolving patterns of multimorbidity.\n\n\nDr Ali H
 assaine is a research fellow in the Division of Informatics\, Imaging an
 d Data Sciences at the University of Manchester where he applies machine
  learning techniques to better understand multimorbidity in the context 
 of metabolic diseases. His research interests include: machine learning\
 , image processing\, text mining and social computing.\n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:G.08\, Chemistry Building\, Manchester
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