Healthcare Process Modelling by Rule Based Networks

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# Healthcare Process Modelling by Rule Based Networks - PowerPoint PPT Presentation

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

Han Liu

First Year PhD Student

Alex Gegov, Jim Briggs, Mohammed Bader

PhD Supervisors

• Health status monitoring
• Treatment recommendation
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

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.
If x1=1 and x2=1 then y1=1

Medical Rules

Patient Features

Medical Features

Figure 2