Now showing items 1-5 of 5

    • Explanation Ontology in Action: A Clinical Use-Case 

      Chari, Shruthi; Seneviratne, Oshani; Gruen, Daniel; Foreman, Morgan; Das, Amar; McGuinness, Deborah L. (2020-11-01)
      We addressed the problem of a lack of semantic representation for user-centric explanations and different explanation types in our Explanation Ontology (https://purl.org/heals/eo). Such a representation is increasingly ...
    • Explanation Ontology: A Model of Explanations for User-Centered AI 

      Chari, Shruthi; Seneviratne, Oshani; Gruen, Daniel; Foreman, Morgan; Das, Amar; McGuinness, Deborah L. (2020-11-01)
      Explainability has been a goal for Artificial Intelligence (AI) systems since their conception, with the need for explainability growing as more complex AI models are increasingly used in critical, high-stakes settings ...
    • Making Study Populations Visible through Knowledge Graphs 

      Chari, Shruthi; Qim, Miao; Agu, Nkechinyere; Seneviratne, Oshani; McCusker, Jamie; Bennett, Kristin P.; Das, Amar; McGuinness, Deborah L. (2019-10-12)
    • Ontology-enabled Analysis of Study Populations 

      Chari, Shruthi; Qim, Miao; Agu, Nkechinyere; Seneviratne, Oshani; McCusker, Jamie; Bennett, Kristin P.; Das, Amar; McGuinness, Deborah L. (2019-10-01)
      We address the problem of modeling study populations in research studies in a declarative manner. Research studies often have a great degree of variability in the reporting of population descriptions. To make study populations ...
    • Semantic Modeling of Cohort Descriptions in Research Studies 

      Chari, Shruthi; Weerawarana, Rukmal; Seneviratne, Oshani; McCusker, Jamie; McGuinness, Deborah L.; Das, Amar (2018-10-29)
      Recommendations in ADA’s Standards of Medical Care in Diabetes guideline are supported by findings from scientific publications (primarily clinical trials and case studies). We propose an approach rooted in Information ...