Browsing Tetherless World Publications by Author "Agu, Nkechinyere"

Now showing items 1-9 of 9

    • AnaXNet: Anatomy Aware Multi-label Finding Classification in Chest X-Ray 

      Agu, Nkechinyere; Wu, Joy T.; Chao, Hanqing; Lourentzou, Ismini; Sharma, Arjun; Moradi, Mehdi; Yan, Pingkun; Hendler, James A. (Springer-Verlag, Berlin, Heidelberg, 2021-09-27)
      Radiologists usually observe anatomical regions of chest X-ray images as well as the overall image before making a decision. However, most existing deep learning models only look at the entire X-ray image for classification, ...

    • Chest ImaGenome Dataset for Clinical Reasoning 

      Wu, Joy T.; Agu, Nkechinyere; Lourentzou, Ismini; Sharma, Arjun; Paguio, Joseph A.; Yao, Jasper S.; Dee, Edward C.; Mitchell, William; Kashyap, Satyananda; Giovannini, Andrea; Celi, Leo A.; Moradi, Mehdi (Neural Information Processing Systems, 2021)
      Despite the progress in automatic detection of radiologic findings from Chest X-Ray (CXR) images in recent years, a quantitative evaluation of the explainability of these models is hampered by the lack of locally labeled ...

    • Developing Scientific Knowledge Graphs Using Whyis 

      McCusker, Jamie; Rashid, Sabbir; Agu, Nkechinyere; Bennett, Kristin P.; McGuinness, Deborah L. (SemSci, 2018)
      We present Whyis, the first framework for creating custom provenance-driven knowledge graphs. Whyis knowledge graphs are based on nanopublications, which simplifies and standardizes the production of structured, ...

    • Enabling Trust in Clinical Decision Support Recommendations through Semantics 

      Seneviratne, Oshani; Das, Amar K.; Chari, Shruthi; Agu, Nkechinyere; Rashid, Sabbir; Chen, Ching-Hua; McCusker, Jamie; Hendler, James A.; McGuinness, Deborah L. (CEUR Workshop Proceedings (CEUR-WS.org), 2019)
      In an ideal world, the evidence presented in a clinical guideline would cover all aspects of patient care and would apply to all types of patients; however, in practice, this rarely is the case. Existing medical decision ...

    • G-PROV: Provenance Management for Clinical Practice Guidelines 

      Agu, Nkechinyere; Keshan, Neha; Chari, Shruthi; Seneveratne, Oshani; Rashid, Sabbir; Das, Amar K.; McCusker, Jamie; McGuinness, Deborah L. (CEUR-WS, 2019-10)
      Providing provenance of treatment suggestions made by clinical decision support systems can enhance transparency and trust in these systems by healthcare practitioners. Provenance can aid in resolving ambiguity and conflicts ...

    • Improving Identified Comorbidities using Semantically Annotated Disease Graph 

      Agu, Nkechinyere; Seneviratne, Oshani; McGuinness, Deborah L. (AMIA, 2018-11-08)

    • 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 ...

    • The Whyis Knowledge Graph Framework in Action 

      McCusker, Jamie; Rashid, Sabbir; Agu, Nkechinyere; Bennett, Kristin P.; McGuinness, Deborah L. (2018-10-01)
      We will demonstrate a reusable framework for developing knowledge graphs that supports general, open-ended development of knowledge curation, interaction, and inference. Knowledge graphs need to be easily maintainable and ...