Incorporating Data Mining Applications into Clinical Guidelines
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Transcript of Incorporating Data Mining Applications into Clinical Guidelines
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Incorporating Data Mining Incorporating Data Mining Applications into Clinical GuidelinesApplications into Clinical Guidelines
Reza SherafatReza SherafatDr. Kamran SartipiDr. Kamran Sartipi
Department of Computing and SoftwareDepartment of Computing and SoftwareMcMaster University, CanadaMcMaster University, Canada{sherafr, sartipi}@mcmaster.ca{sherafr, sartipi}@mcmaster.ca
Computer-based Medical Systems (CBMS Computer-based Medical Systems (CBMS ’06)’06)June 22, 2006June 22, 2006
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OutlineOutline
Decision making based on data mining Decision making based on data mining resultsresults
Data and knowledge interoperabilityData and knowledge interoperability Knowledge management frameworkKnowledge management framework Tool implementationTool implementation ConclusionConclusion
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Decision MakingDecision Making
Practitioners face critical questions which Practitioners face critical questions which requires decision making:requires decision making:
– The cause of a symptomThe cause of a symptom
– Drug prescriptionDrug prescription
– Treatment planningTreatment planning– Diagnosis of a diseaseDiagnosis of a disease– … … (many more)(many more)
Clinical Decision Support Systems (CDSS)Clinical Decision Support Systems (CDSS)– Computer programsComputer programs
– Provide online and Provide online and patient-specific assistance patient-specific assistance to health care professionals to health care professionals to make better decisionsto make better decisions
– Clinical knowledge is stored Clinical knowledge is stored in a knowledge-basein a knowledge-base
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Data Mining ApplicationsData Mining Applicationsin Health carein Health care
Patient
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Decision LogicDecision Logic
IFIF
the patient has had a heart stroke and is the patient has had a heart stroke and is above 50 above 50
THENTHEN
his health condition should be monitored!his health condition should be monitored!
Condition
Action
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Decision Logic (cont’d)Decision Logic (cont’d)
Decision making logic:Decision making logic:
– Logical expressionsLogical expressions ‘‘If-then-elseIf-then-else’’ structures structures
– Test for conditionsTest for conditions– Trigger actionsTrigger actions
if ( (patient.age > 50) && if ( (patient.age > 50) && (patient.previous_heart_stroke == true) (patient.previous_heart_stroke == true) ))
then …then …
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Data Mining Decision LogicData Mining Decision Logic Data miningData mining
– Analysis and mining of data to extract hidden facts in Analysis and mining of data to extract hidden facts in the datathe data
– The extracted facts are represented in a data The extracted facts are represented in a data structure called structure called “data mining model”“data mining model”
TrainingTraining vs. vs. ApplicationApplication of a data mining model: of a data mining model:– Training the model: Building the modelTraining the model: Building the model– Application of the mode: interpreting for specific Application of the mode: interpreting for specific
patient datapatient data
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Data Mining Decision Logic (cont’d)Data Mining Decision Logic (cont’d) ClassificationClassification: mapping data into predefined classes. : mapping data into predefined classes.
(e.g., whether a patient has a specific disease or not)(e.g., whether a patient has a specific disease or not)
RegressionRegression: mapping a data item to a real-valued : mapping a data item to a real-valued prediction variable. (e.g., prediction variable. (e.g., planning treatments.)planning treatments.)
ClusteringClustering: To identify clusters of data items. (e.g., to : To identify clusters of data items. (e.g., to cluster patients based on risk factors.)cluster patients based on risk factors.)
Association RuleAssociation Rule MiningMining: to find hidden associations in : to find hidden associations in the data set (e.g., how different patient data are related the data set (e.g., how different patient data are related based on shared relations such as: “specific diseases”, based on shared relations such as: “specific diseases”, “patients habits”, or “family disease history”.)“patients habits”, or “family disease history”.)
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Data Mining Decision Logic (cont’d)Data Mining Decision Logic (cont’d)
An example of regression model An example of regression model [source:Otto,Pearlmen][source:Otto,Pearlmen]
Vmax
Doppler AVA
AVR not recommendedAVR recommended
AI severity
≥4m/s3-4m/s
≤ 3m/s
≤ 1 cm2 ≥1.7 cm21.1-1.6 cm2
2-3+ %100%100
%66
0-1+
%100
%100
%88
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Application of Data Mining ResultsApplication of Data Mining Results
Predictive Model Markup Language (Predictive Model Markup Language (PMMLPMML):):– XMLXML based specification based specification– Meta modelMeta model: Define the data structure of the model: Define the data structure of the model– Different types Different types of data mining models (clustering, of data mining models (clustering,
classifications, …)classifications, …)– ExtendableExtendable for model specific constructs for model specific constructs
Share, access, exchange PMML documentsShare, access, exchange PMML documents
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Proposed Health Care Proposed Health Care Knowledge Management FrameworkKnowledge Management Framework
Guideline modeling
Knowledge Extraction
Guideline Execution
Phase 1: Phase 1: Build the data mining modelsBuild the data mining models
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Proposed Health Care Proposed Health Care Knowledge Management FrameworkKnowledge Management Framework
Data and knowledgeinteroperability
Knowledge Extraction
Guideline Execution
Phase 2: Phase 2: Encode data and knowledgeEncode data and knowledge
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Proposed Health Care Proposed Health Care Knowledge Management FrameworkKnowledge Management Framework
Data and knowledgeinteroperability
Knowledge Extraction
Knowledge Interpretation
Phase 3: Phase 3: Apply the knowledge for specific Apply the knowledge for specific patient datapatient data
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Knowledge
Data and Knowledge InteroperabilityData and Knowledge Interoperability
HL-7 Reference Information Model (HL-7 Reference Information Model (RIMRIM))– A general high level health care data model A general high level health care data model
Clinical Document Architecture (Clinical Document Architecture (CDACDA))– An XML-based standard for defining structured templates for An XML-based standard for defining structured templates for
clinical documentsclinical documents
Standard Terminology Systems (Standard Terminology Systems (UMLS, SNOMED CT, UMLS, SNOMED CT, etc)etc)– Standard clinical vocabulary setsStandard clinical vocabulary sets
Predictive Model Markup Language (Predictive Model Markup Language (PMMLPMML))– An XML-based standard for representing data mining resultsAn XML-based standard for representing data mining results
Guideline Interchange Format 3 (Guideline Interchange Format 3 (GLIF3GLIF3))– A clinical guideline definition standardA clinical guideline definition standard
Data
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Tool ImplementationTool Implementation A guideline execution engine based on GLIFA guideline execution engine based on GLIF Logic modules apply data mining models and Logic modules apply data mining models and
are accessed through web services technologyare accessed through web services technology Provides additional information to help guide the Provides additional information to help guide the
flow in the guideline.flow in the guideline.
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ConclusionConclusion Data mining results can be used as a source of Data mining results can be used as a source of
knowledge to help clinical decision making.knowledge to help clinical decision making.
We described an approach to apply different types of We described an approach to apply different types of data mining models in CDSS.data mining models in CDSS.
We used PMML and CDA for knowledge and data We used PMML and CDA for knowledge and data representation.representation.
A tool is developed that can interpret and apply the A tool is developed that can interpret and apply the mined knowledge.mined knowledge.
We envision a future that data mining analysis results We envision a future that data mining analysis results are seamlessly deployed and used at usage sites.are seamlessly deployed and used at usage sites.
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Questions and CommentsQuestions and Comments