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PRODID:-//Columba Systems Ltd//NONSGML CPNG/SpringViewer/ICal Output/3.3-
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CALSCALE:GREGORIAN
METHOD:PUBLISH
BEGIN:VEVENT
DTSTAMP:20140317T143953Z
DTSTART:20140318T130000Z
DTEND:20140318T140000Z
SUMMARY:An Introduction to Text Mining
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}nrn-hsoq030
 q-91zguu
DESCRIPTION:This seminar is part of the CHSTM Lunchtime Seminar Series   
                                                                         
                                                                         
                                                                         
                                                                         
                                                                         
                                                                         
                                                                         
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                                                                  \nAn In
 troduction to Text Mining\n\nText mining (TM) is the process of discover
 ing and extracting knowledge from unstructured textual data. This includ
 es the recognition of entities in the texts\, e.g.\, diseases\, symptoms
 \, drugs etc.\, together with the identification of relationships that o
 ccur amongst them e.g.\, which drugs have been used to treat a particula
 r disease. Based on the knowledge extracted\, associations can be found 
 amongst the pieces of information extracted from many different texts\, 
 e.g. how successful are different drugs in treating particular diseases 
 and under what conditions?\nTM is becoming increasingly important with t
 he advent of "big data".  The sheer volume of available digital textual 
 data means that\, without suitable TM tools that can assist in the searc
 h for relevant information and discovery of trends\, there is a danger t
 hat much important information will be overlooked.  Big data has resulte
 d not only from the exponential growth in the rate at which new scientif
 ic papers are being published\, but also from increased efforts to digit
 ise historical documents. The availability of digitised historical archi
 ves provides researchers with a potentially rich source of data to study
  trends over long periods of time\, such as changes in treatments and un
 derstanding of diseases.  The search for and study of relevant relations
 hips between entities that occur within these documents can be vastly ai
 ded by the availability of powerful TM tools. This talk provides an intr
 oduction to some of the techniques used in the development of TM systems
 \, and examines a number of different tools that have been developed for
  application to biomedical text.  We consider how such tools could be us
 ed and adapted to assist in the study and discovery of information withi
 n historical medical documents. \n\n \n
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:2.57\, Simon Building\, Manchester
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