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VERSION:2.0
PRODID:-//University of Liverpool Computer Science Seminar System//v2//EN
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DTSTAMP:20260921T003438Z
UID:Seminar-DMML-530@lxserverM.csc.liv.ac.uk
ORGANIZER:CN=Danushka Bollegala:MAILTO:Danushka.Bollegala@liverpool.ac.uk
DTSTART:20180420T110000
DTEND:20180420T120000
SUMMARY:Data Mining and Machine Learning Series
DESCRIPTION:Graeme Kirkwood: EPR and big data research in clinical cardiology –challenges and collaborative opportunities\n\nClinical cardiology is a data-rich domain, constituting multiple sources ranging from structured and unstructured electronic patient records (EPR), through coded outcome measures, to direct downloads from implantable cardiac devices such as pacemakers. Until recently, research into disease management and outcomes has been hampered by limitations of coding completeness and accuracy; it is hoped that this can be improved by establishing collaborative links between clinical specialists and big data experts. As an illustration of what might be achieved, this talk considers preliminary work on the Manchester Adult Congenital Heart Disease population and the challenges faced with establishing an EPR text mining project.\n\nhttps://www.csc.liv.ac.uk/research/seminars/abstract.php?id=530
LOCATION:EEE 5.07
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