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GLINDA: Automated Reasoning for Application of Clinical Guidelines BMIR Research-in-Progress Presentation Csongor Nyulas Samson Tu
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Acknowledgement Funder: National Library of Medicine Project Members Mark Musen Mary Goldstein Susana Martins Hyunggu Jung Pamela Kum
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Problem Statement Populations are aging worldwide Older adults tend to have multiple chronic conditions Data?? Management of multiple comorbidities presents a challenging problem Almost all clinical practice guidelines focus on the management of single diseases May take comorbidities into account Simultaneous application of multiple guidelines leads to suboptimal care
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Research Goals Develop a modular and extensible platform for exploring informatics and clinical issues Integrate and reuse best-of-breed knowledge resources and applications Create methods for detecting, repairing and integrating treatment recommendations from multiple guideliens
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Method Adapt BioSTORM agent architecture Task decomposition Problem-solving method Reuse ATHENA CDSS Clinical domains: Hypertension, diabetes mellitus, heart failure, hyperlipidemia, chronic kidney disease Develop new agents for detecting, repairing, and integrating treatment recommendations Apply methods on anonymized patient cases from the Stanford STRIDE database
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Outline of Method Section STRIDE patient selection and preparation BioSTORM agent architecture and its application to GLINDA ATHENA DSS agents New agents for detecting, repairing and integrating guideline recommendations Presentation for review
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STRIDE Patient Extraction
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Test Patients Selection
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Data Preparation
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BioSTORM Agent Architecture
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GLINDA Agent Configurations
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ATHENA CDSS
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Integrating Recommendations from Multiple Guidelines
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Detecting Interactions
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Current Status
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Future Work
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