Healthcare Process Modelling by Rule Based Networks

Han Liu First Year PhD Student

Alex Gegov, Jim Briggs, Mohammed BaderPhD Supervisors

Table of contents

• Health status monitoring• Treatment recommendation

Health Status Monitoring• 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 in Figure 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

If x1=1 and x2=1 then y=1

Treatment Recommendation 1. To classify patients into a particular category based on similarity

using K Nearest Neighbour.2. To retrieve treatments that have been applied to previous patients

classified into the same category as the current patient and find a list of candidate treatments by majority voting.

3. To classify these candidate treatments to one of rate scale of 1 to k and filter those treatments with negative classification.

4. 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 in Figure 2.

5. 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

Patient Features Medical Rules Medical Features

Figure 2

Thank you