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Healthcare Process Modelling by Rule Based Networks

Healthcare Process Modelling by Rule Based Networks. Han Liu First Year PhD Student Alex Gegov , Jim Briggs, Mohammed Bader PhD Supervisors. Table of contents. Health status monitoring Treatment recommendation. Health Status Monitoring. If x1=1 and x2=1 then y=1.

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Healthcare Process Modelling by Rule Based Networks

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  1. Healthcare Process Modelling by Rule Based Networks Han Liu First Year PhD Student Alex Gegov, Jim Briggs, Mohammed Bader PhD Supervisors

  2. Table of contents • Health status monitoring • Treatment recommendation

  3. Health Status Monitoring If x1=1 and x2=1 then y=1 • A set of medical rules used to predict health status is generated by a rule generation algorithm learning historical data and then converted into network structure illustrated inFigure 1 • Each node in input layer represents a medical feature • Each node in middle layer represents a medical rule • The output node represents the classification of health status, e.g. in risk or health input conjunction output Figure 1

  4. TreatmentRecommendation • To classify patients into a particular category based on similarity using K Nearest Neighbour. • To retrieve treatments that have been applied to previous patients classified into the same category as the currentpatient and find a list of candidate treatments by majority voting. • To classify these candidate treatments to one of rate scale of 1 to k and filter those treatments with negative classification. • To induce a list of association rules which have patient features on left hand side and medical features on right hand side and is represented by a network as illustrated inFigure 2. • To retrieve a list of most potential treatments that match the features represented by the right hand sides of association rules in order to recommend doctors a list of candidate choices.

  5. If x1=1 and x2=1 then y1=1 Medical Rules Patient Features Medical Features Figure 2

  6. Thank you

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