Browsing Tetherless World Publications by Issue Date

Now showing items 41-60 of 734

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • Cluster Analysis of Presolar Silicon Carbide Grains: Evaluation of Their Classification and Astrophysical Implications 

      Boujibar, Asmaa; Howell, Samantha; Zhang, Shuang; Hystad, Grethe; Prabhu, Anirudh; Liu, Nan; Stephan, Thomas; Narkar, Shweta; Eleish, Ahmed; Morrison, Shaunna M.; Hazen, Robert; Nittler, Larry R. (AAS/IOP, 2021-06)
      Cluster analysis of presolar silicon carbide grains based on literature data for 12C/13C, 14N/15N, δ30Si/28Si, and δ29Si/28Si including or not inferred initial 26Al/27Al data, reveals nine clusters agreeing with previously ...

    • The Personal Health Library: Taking EHR design to the Next Level 

      Ammar, Nariman; Seneviratne, Oshani; Bailey, James; Davis, Robert; McGuinness, Deborah L.; Shaban-Nejad, Arash (The Knowledge Graph Conference, 2021-05)
      Technology maturation in EHR design has evolved over the years. Formal data semantics and rich knowledge encoded in ontologies lead to new era of personalized precision medicine. Also, Web technologies have enabled EHRs ...

    • Unmasking the conversation on masks: Natural language processing for topical sentiment analysis of COVID-19 Twitter discourse 

      Sanders, Abraham; White, R. C.; Severson, L. S.; Ma, R.; McQueen, R.; Alcântara Paulo, H. C.; Zhang, Y.; Erickson, John S.; Bennett, Kristin P. (AMIA, 2021-05)
      In this exploratory study, we scrutinize a database of over one million tweets collected from March to July 2020 to illustrate public attitudes towards mask usage during the COVID-19 pandemic. We employ natural language ...

    • Applying Personal Knowledge Graphs to Health 

      Shirai, Sola; Seneviratne, Oshani; McGuinness, Deborah L. (arXiv, 2021-04)
      Knowledge graphs that encapsulate personal health information, or personal health knowledge graphs (PHKG), can help enable personalized health care in knowledge-driven systems. In this paper we provide a short survey of ...

    • Model LineUpper: Supporting Interactive Model Comparison at Multiple Levels for AutoML 

      Narkar, S.; Zhang, Y.; Liao, Q. V.; Wang, D.; Weisz, J. D. (ACM, 2021-04)
      Automated Machine Learning (AutoML) is a rapidly growing set of technologies that automate the model development pipeline by searching model space and generating candidate models. A critical, final step of AutoML is human ...

    • Capturing Row and Column Semantics in Transformer Based Question Answering over Tables 

      Glass, Michael; Canim, Mustafa; Gliozzo, Alfio; Chemmengath, Saneem; Kumar, Vishwajeet; Chakravarti, Rishav; Sil, Avi; Pan, FeiFei; Bharadwaj, Samarth; Fauceglia, Nicolas Rodolfo (arXiv, 2021-04)
      Transformer based architectures are recently used for the task of answering questions over tables. In order to improve the accuracy on this task, specialized pre-training techniques have been developed and applied on ...