Toward a standard formal semantic representation of the model card report.

Journal: BMC bioinformatics
Published Date: Jul 14, 2022

Abstract

BACKGROUND: Model card reports aim to provide informative and transparent description of machine learning models to stakeholders. This report document is of interest to the National Institutes of Health's Bridge2AI initiative to address the FAIR challenges with artificial intelligence-based machine learning models for biomedical research. We present our early undertaking in developing an ontology for capturing the conceptual-level information embedded in model card reports.

Authors

  • Muhammad Tuan Amith
    University of North Texas, USA.
  • Licong Cui
    The University of Texas Health Science Center at Houston, USA.
  • Degui Zhi
    School of Biomedical Informatics, the University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Kirk Roberts
    The University of Texas Health Science Center at Houston, USA.
  • Xiaoqian Jiang
    School of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
  • Fang Li
    Department of General Surgery, Chongqing General Hospital, Chongqing, China.
  • Evan Yu
    School of Biomedical Informatics, University of Texas Health Science Center, Houston, TX, USA.
  • Cui Tao
    The University of Texas Health Science Center at Houston, USA.

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