Computational Reasoning across Multiple Models

Guy Tsafnat*, Enrico W. Coiera

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


Computational support of clinical decisions frequently requires the integration of data in a variety of formats and from multiple sources and domains. Some impressive multiscale computational models of biological phenomena have been developed as part of the study of disease and healthcare systems. One can now contemplate harnessing these models arising from computational biology and using highly interconnected clinical data to support clinical decision-making. Indeed, understanding how to build computational systems able to reason across heterogeneous models and datasets is one of the major and perhaps foundational challenges of translational biomedical informatics. In this paper, the authors examine the use of multimodels (models composed of several daughter models) and explore three major research challenges to reasoning across multiple models: model selection, model composition, and computer aided model construction.

Original languageEnglish
Pages (from-to)768-774
Number of pages7
JournalJournal of the American Medical Informatics Association
Issue number6
Publication statusPublished - Nov 2009
Externally publishedYes


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