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      Temporal Discovery Workbench: a Case Study with ICU Patient Datasets

      1 , 2 , 1 , 2 ,

      BCS Health Informatics Scotland (HIS) (HIS)

      BCS Health Informatics Scotland (HIS)

      2 - 3 September 2014

      Modelling of Expertize, Temporal Datasets, Event Prediction, Workbench, Intensive Care Unit, Myocardial Damage

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          Temporal datasets are now often collected and curated in industry, scientific labs, and healthcare. A considerable amount of work has been done to analyze these for trends, inconsistencies and to make use of them for prediction. In an earlier study we discussed datasets for 15 or so Intensive Care Unit patients with clinicians, and asked them if they could detect when a particular harmful event (a myocardial infarction) had occurred. After 3 lengthy knowledge capture sessions we formulated a complex model to identify myocardial damage which we then implemented and tested against a test dataset; a detection rate of approximately 80% was achieved. (Specifically the model suggests that several events generally occur in a temporal sequence before the event-to-be-predicted occurs.) This work reports the design of a Temporal Discovery Workbench (TDWB) to address this class of tasks and has reproduced the results of the initial model acquired from the experts. Further we have now run TDWB's pattern discovery module with a range of settings to see if further clinically useful patterns are reported. Initial results are encouraging.

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          Most cited references 2

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          A survey of temporal data mining

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            A System to Detect Inconsistencies between a Domain Expert’s Different Perspectives on (Classification) Tasks


              Author and article information

              September 2014
              September 2014
              : 1-7
              [1 ]Dept. of Computing Sc.,

              University of Aberdeen,

              Aberdeen, AB24 3UE
              [2 ]School of Medicine,

              University of Glasgow,

              Glasgow, G31 2ER
              School of Medicine,

              University of Glasgow,

              Glasgow, G31 2ER
              © Derek Sleeman et al. Published by BCS Learning and Development Ltd. BCS Health Informatics Scotland (HIS), Glasgow, UK

              This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit

              BCS Health Informatics Scotland (HIS)
              Glasgow, UK
              2 - 3 September 2014
              Electronic Workshops in Computing (eWiC)
              BCS Health Informatics Scotland (HIS)
              Product Information: 1477-9358BCS Learning & Development
              Self URI (journal page):
              Electronic Workshops in Computing


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