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

Muhammad Tuan AmithLicong CuiDegui ZhiKirk RobertsXiaoqian JiangFang LiEvan YuCui Tao
Published in: BMC bioinformatics (2022)
The benefit of our work is that it utilizes expansive and standard terminologies and scientific rigor promoted by biomedical ontologists, as well as, generating an avenue to make model cards machine-readable using semantic web technology. Our future goal is to assess the veracity of our model and later expand the model to include additional concepts to address terminological gaps. We discuss tools and software that will utilize our ontology for potential application services.
Keyphrases
  • healthcare
  • primary care
  • mental health
  • deep learning
  • risk assessment
  • climate change
  • neural network