Now showing items 41-60 of 741

    • InDO: the Institute Demographic Ontology 

      Keshan, Neha; Fontaine, Kathy; Hendler, James A. (Springer, Cham, 2021-11-22)
      Graduate education institutes in the United States (US) have been working on programs to increase the number of students and faculty from marginalized communities. When choosing to pursue a doctoral degree, the common ...
    • Towards Clinically Relevant Explanations for Type-2 Diabetes Risk Prediction with the Explanation Ontology 

      Chari, Shruthi; Chakraborty, Prithwish; Seneviratne, Oshani; Ghalwash, Mohamed; Gruen, Daniel M.; Sow, Daby; McGuinness, Deborah L. (AMIA, 2021-11)
    • Enhancing Clinical Relevance of Health Behavior Insights via Semantics 

      Harris, Jonathan; McGuinness, Deborah L.; Monti, Marco; Seneviratne, Oshani; Zaki, Mohammed J.; Chen, Ching-Hua (AMIA, 2021-11)
    • Geospatial Reasoning with shapefiles for Supporting Policy Decisions 

      Santos, Henrique; McCusker, Jamie; McGuinness, Deborah L. (2021-10-12)
      Policies are authoritative assets that are present in multiple domains to support decision-making. They describe what actions are allowed or recommended when domain entities and their attributes satisfy certain criteria. ...
    • Dimensions of Commonsense Knowledge 

      Ilievski, Filip; Oltramari, Alessandro; Ma, Kaixin; Zhang, Bin; McGuinness, Deborah L.; Szekely, Pedro (Knowledge-Based Systems, 2021-10-11)
      Commonsense knowledge is essential for many AI applications, including those in natural language processing, visual processing, and planning. Consequently, many sources that include commonsense knowledge have been designed ...
    • The Punya Platform: Building Mobile Research Apps with Linked Data and Semantic Features 

      Patton, E.W.; Van Woensel, W.; Seneviratne, Oshani; Loseto, G.; Scioscia, F.; Kagal, L. (Springer, Cham, 2021-10)
      Modern smartphones offer advanced sensing, connectivity, and processing capabilities for data acquisition, processing, and generation: but it can be difficult and costly to develop mobile research apps that leverage these ...
    • BlockIoT: Blockchain-based Health Data Integration using IoT Devices 

      Shukla, Manan; Lin, Jianjing; Seneviratne, Oshani (arXiv, 2021-10)
      The development and adoption of Electronic Health Records (EHR) and health monitoring Internet of Things (IoT) Devices have enabled digitization of patient records and has also substantially transformed the healthcare ...
    • Personal Health Knowledge Graph for Clinically Relevant Diet Recommendations 

      Seneviratne, Oshani; Harris, Jonathan; Chen, Ching-Hua; McGuinness, Deborah L. (AKBC, 2021-10)
      We propose a knowledge model for capturing dietary preferences and personal context to provide personalized dietary recommendations. We develop a knowledge model called the Personal Health Ontology, which is grounded in ...
    • 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, ...
    • The Problem of Fairness in Synthetic Healthcare Data 

      Bhanot, Karan; Qi, Miao; Erickson, John S.; Guyon, Isabelle; Bennett, Kristin P. (Entropy (Basel, Switzerland), 2021-09)
      Access to healthcare data such as electronic health records (EHR) is often restricted by laws established to protect patient privacy. These restrictions hinder the reproducibility of existing results based on private ...
    • Knowledge Graphs 

      Hogan, Aidan; Gutierrez, Claudio; Cochcz, Michael; de Melo, Gerard; Kirranc, Sabrina; Pollcrcs, Axel; Navigli, Roberto; Ngonga Ngomo, Axcl-Cyrille; Rashid, Sabbir; Schmclzciscn, Lukas; Staab, Stefan; Blomqvist, Eva; d’Amato, Claudia; Gayo, José Emilio Labra; Ncumaicr, Sebastian (Springer, Cham, 2021-09)
      This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying ...
    • International Workshop on Knowledge Graph: Heterogenous Graph Deep Learning and Applications 

      Unknown author (ACM, 2021-08)
      Knowledge graph (KG) is the backbone to enable cognitive Artificial Intelligence (AI), which relies on cognitive computing and semantic reasoning. Knowledge graph is the connected data with the semantically enriched context. ...
    • Leveraging Clinical Context for User-Centered Explainability: A Diabetes Use Case 

      Chari, Shruthi; Chakraborty, Prithwish; Ghalwash, Mohamed; Seneviratne, Oshani; Eyigöz, Elif; Gruen, Daniel; Suarez Saiz, Fernando; Chen, Ching Hua; Meyer Rojas, Pablo; McGuinness, Deborah L. (CoRR, 2021-07-01)
      Academic advances of AI models in high-precision domains, like healthcare, need to be made explainable in order to enhance real-world adoption. Our past studies and ongoing interactions indicate that medical experts can ...
    • Immunogenicity of PCV24, an expanded pneumococcal conjugate vaccine, in adult monkeys and protection in mice 

      McGuinness, Deborah L.; Kaufhold, Robin M.; McHugh, Patrick M.; Winters, Michael A.; Smith, William J.; Giovarelli, Cecilia; He, Jian; Zhang, Yuhua; Musey, Luwy; Skinner, Julie M. (2021-07)
      Invasive pneumococcal disease (IPD) is responsible for serious illnesses such as bacteremia, sepsis, meningitis, and pneumonia in young children, older adults, and persons with immunocompromising conditions and often leads ...
    • An experimental study measuring human annotator categorization agreement on commonsense sentences 

      Santos, Henrique; Kejriwal, Mayank; Mulvehill, Alice; Forbush, Gretchen; McGuinness, Deborah L. (Experimental Results, 2021-06-18)
      Developing agents capable of commonsense reasoning is an important goal in Artificial Intelligence (AI) research. Because commonsense is broadly defined, a computational theory that can formally categorize the various kinds ...
    • Building a Social Machine for Graduate Mobility 

      Keshan, Neha (13th ACM Web Science Conference 2021, 2021., 2021-06-01)
      The paper discusses the construction of a social machine to solve a complex problem faced by doctoral students: “What Comes Next?” especially important during this pandemic when many traditional career paths have been ...
    • Towards a Domain-Agnostic Computable Policy Tool 

      Falkow, Mitchell; Santos, Henrique; McGuinness, Deborah L. (2021-06-01)
      Policies are often crucial for decision-making in a wide range of domains. Typically they are written in natural language, which leaves room for different individual interpretations. In contrast, computable policies offer ...
    • Temporal Analysis of Social Determinants Associated with COVID-19 Mortality 

      Debopadhaya, Shayom; Erickson, John S.; Bennett, Kristin P. (2021-06)
      This study examines how social determinants associated with COVID-19 mortality change over time. Using US county-level data from July 5 and December 28, 2020, the effect of 19 high-risk factors on COVID-19 mortality rate ...
    • WebSci 21 Companion 

      Seneviratne, Oshani; Singh, V.; Freire, A.; Luo, J. D. (ACM, 2021-06)
    • CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answering 

      Pan, FeiFei; Canim, Mustafa; Glass, M.; Gliozzo, A.; Fox, Peter (arXiv, 2021-06)
      We present the first end-to-end, transformer-based table question answering (QA) system that takes natural language questions and massive table corpus as inputs to retrieve the most relevant tables and locate the correct ...