ArticleLearning health systems2023
CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.
Article in Learning health systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- The Potential for a Benefit-Estimating Algorithm to Improve Recommendations for Preventive Services: Comparing Algorithm Recommendations with Those of Primary Care Providers.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- A prototype ETL pipeline that uses HL7 FHIR RDF resources when deploying pure functions to enrich knowledge graph patient data.Journal of biomedical semantics · 2025Article
- Ten simple rules to make computable knowledge shareable and reusable.PLoS computational biology · 2024Article
- An LLM-Powered Clinical Calculator Chatbot Backed by Verifiable Clinical Calculators and their Metadata.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Modeling Precision Feedback Knowledge for Healthcare Professional Learning and Quality Improvement.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- CBK model composition using paired web services and executable functions: A demonstration for individualizing preventive services.Learning health systems · 2023Article
- Personalized Disease Prevention (PDP): study protocol for a cluster-randomized clinical trial.Trials · 2022Article
Corrections and comments
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Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
Introduction: Learning health systems are challenged to combine computable biomedical knowledge (CBK) models. Using common technical capabilities of the World Wide Web (WWW), digital objects called Knowledge Objects, and a new pattern of activating CBK models brought forth here, we aim to show that it is possible to compose CBK models in more highly standardized and potentially easier, more useful ways. Methods: Using previously specified compound digital objects called Knowledge Objects, CBK models are packaged with metadata, API descriptions, and runtime requirements. Using open-source runtimes and a tool we developed called the KGrid Activator, CBK models can be instantiated inside runtimes and made accessible via RESTful APIs by the KGrid Activator. The KGrid Activator then serves as a gateway and provides a means to interconnect CBK model outputs and inputs, thereby establishing a CBK model composition method. Results: To demonstrate our model composition method, we developed a complex composite CBK model from 42 CBK submodels. The resulting model called CM-IPP is used to compute life-gain estimates for individuals based their personal characteristics. Our result is an externalized, highly modularized CM-IPP implementation that can be distributed and made runnable in any common server environment. Discussion: CBK model composition using compound digital objects and the distributed computing technologies is feasible. Our method of model composition might be usefully extended to bring about large ecosystems of distinct CBK models that can be fitted and re-fitted in various ways to form new composites. Remaining challenges related to the design of composite models include identifying appropriate model boundaries and organizing submodels to separate computational concerns while optimizing reuse potential. Conclusion: Learning health systems need methods for combining CBK models from a variety of sources to create more complex and useful composite models. It is feasible to leverage Knowledge Objects and common API methods in combination to compose CBK models into complex composite models.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.