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CBK model composition using paired web services and executable functions: A demonstration for individualizing

Allen Flynn1, Glen Taksler2, Tanner Caverly1

  • 1Department of Learning Health Sciences Medical School University of Michigan Ann Arbor Michigan USA.

Learning Health Systems
|April 17, 2023
PubMed
Summary
This summary is machine-generated.

This study demonstrates a feasible method for composing computable biomedical knowledge (CBK) models using Knowledge Objects and web technologies. This approach enables standardized, reusable, and modular composite CBK models for learning health systems.

Keywords:
computable biomedical knowledgedecentralized web technologymodel composition

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Area of Science:

  • Biomedical Informatics
  • Computational Biology
  • Health Systems Science

Background:

  • Learning health systems require integrated computable biomedical knowledge (CBK) models.
  • Existing methods for combining CBK models are often complex and non-standardized.
  • There is a need for more efficient and modular approaches to CBK model composition.

Purpose of the Study:

  • To present a novel method for composing CBK models using Knowledge Objects and World Wide Web (WWW) technologies.
  • To demonstrate the feasibility of creating standardized and reusable composite CBK models.
  • To facilitate the integration of diverse CBK models within learning health systems.

Main Methods:

  • Utilized compound digital objects called Knowledge Objects, encapsulating CBK models with metadata and runtime requirements.
  • Developed the KGrid Activator tool to instantiate CBK models within open-source runtimes and expose them via RESTful APIs.
  • Established a CBK model composition method by interconnecting model inputs and outputs through the KGrid Activator.

Main Results:

  • Successfully developed a complex composite CBK model (CM-IPP) from 42 submodels to estimate life-gain.
  • Created an externalized, highly modularized CM-IPP implementation runnable in standard server environments.
  • Demonstrated the feasibility of composing CBK models using Knowledge Objects and distributed computing.

Conclusions:

  • CBK model composition is feasible using Knowledge Objects and distributed computing technologies.
  • The proposed method supports the creation of large ecosystems of adaptable and reusable CBK models.
  • Future work should focus on optimizing model boundaries and submodel organization for enhanced reusability.