Application of an ontology for model cards to generate computable artifacts for linking machine learning information from biomedical research.
Proc Int World Wide Web Conf
; 2023(Companion): 820-825, 2023 Apr.
Article
em En
| MEDLINE
| ID: mdl-38327770
ABSTRACT
Model card reports provide a transparent description of machine learning models which includes information about their evaluation, limitations, intended use, etc. Federal health agencies have expressed an interest in model cards report for research studies using machine-learning based AI. Previously, we have developed an ontology model for model card reports to structure and formalize these reports. In this paper, we demonstrate a Java-based library (OWL API, FaCT++) that leverages our ontology to publish computable model card reports. We discuss future directions and other use cases that highlight applicability and feasibility of ontology-driven systems to support FAIR challenges.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Proc Int World Wide Web Conf
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Estados Unidos
País de publicação:
Holanda