Browsing Tetherless World Publications by Author "McGuinness, Deborah L."
Now showing items 1-20 of 288
-
Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes
Chari, Shruthi; Acharya, Prasant; Gruen, Daniel M.; Zhang, Olivia; Eyigoz, Elif K.; Ghalwash, Mohamed; Seneviratne, Oshani; Saiz, Fernando Suarez; Meyer, Pablo; Chakraborty, Prithwish; McGuinness, Deborah L. (Elsevier, 2023-02)Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are supported by ‘contextual explanations’ that let the practitioner connect system inferences to their context of use. However, their ... -
Semantic Technologies for Clinically Relevant Personal Health Applications
Chen, Ching-Hau; Gruen, Daniel; Harris, Jonathan; Hendler, James A.; McGuinness, Deborah L.; Monti, Marco; Rastogi, Nidhi; Seneviratne, Oshani; Zaki, Mohammed J (Springer, 2022-11-23)Despite recent advances in digital health solutions and machine learning, personal health applications that aim to modify health behaviors are still limited in their ability to offer more personalized decision support. ... -
Knowledge Graph Construction from Data, Data Dictionaries, and Codebooks: the National Health and Nutrition Examination Surveys Use Case
Santos, Henrique; Pinheiro, Paulo; McGuinness, Deborah L. (2022-09-29)CDC’s National Health and Nutrition Examination Surveys (NHANES) is a continuous survey that aims to study the relationship between diet, nutrition, and health and their roles in designated population subgroups with selected ... -
Differences in Cancer Phenotypes Among Frequent CHEK2 Variants and Implications for Clinical Care—Checking CHEK2
Bychkovsky, Brittany L; Agaoglu, Nihat B; Horton, Carolyn; Zhou, Jing; Yussuf, Amal; Hemyari, Parichehr; Richardson, Marcy E; Young, Colin; LaDuca, Holly; McGuinness, Deborah L.; Scheib, Rochelle; Garber, Judy E; Rana, Huma Q (JAMA Oncol., 2022-09-22)Importance Germline CHEK2 pathogenic variants (PVs) are frequently detected by multigene cancer panel testing (MGPT), but our understanding of PVs beyond c.1100del has been limited. Objective To compare cancer phenotypes ... -
An Ontology for Fairness Metrics
Franklin, Jade S; Bhanot, Karan; Ghalwash, Mohamed; Bennett, Kristin P.; McCusker, Jamie; McGuinness, Deborah L. (ACM, 2022-07)Recent research has revealed that many machine-learning models and the datasets they are trained on suffer from various forms of bias, and a large number of different fairness metrics have been created to measure this bias. ... -
FAIR and Interactive Data Graphics from a Scientific Knowledge Graph
Deagen, Michael E.; McCusker, Jamie; Fateye, Tolulomo; Stouffer, Samuel; Brinson, L. Cate; McGuinness, Deborah L.; Schadler, Linda S. (Nature Scientific Data, 2022-05)Graph databases capture richly linked domain knowledge by integrating heterogeneous data and metadata into a unified representation. Here, we present the use of bespoke, interactive data graphics (bar charts, scatter plots, ... -
Designing a strong test for measuring true common-sense reasoning
Kejriwal, Mayank; Santos, Henrique; Mulvehill, Alice; McGuinness, Deborah L. (Nature Machine Intelligence, 2022-04-22)Common-sense reasoning has recently emerged as an important test for artificial general intelligence, especially given the much-publicized successes of language representation models such as T5, BERT and GPT-3. Currently, ... -
Understanding Clinician Workflows to Design AI Risk Prediction Models
Zhang, O.; Chari, Shruthi; Saiz, F. S.; Gruen, Daniel; Acharya, P.; Seneviratne, Oshani; Meter, P.; McGuinness, Deborah L.; Chakraborty, P. (AMIA, 2022-04) -
A Theoretically Grounded Benchmark for Evaluating Machine Commonsense
Santos, Henrique; Shen, Ke; Mulvehill, Alice M.; Razeghi, Yasaman; McGuinness, Deborah L.; Kejriwal, Mayank (arXiv, 2022-03)Programming machines with commonsense reasoning (CSR) abilities is a longstanding challenge in the Artificial Intelligence community. Current CSR benchmarks use multiple-choice (and in relatively fewer cases, generative) ... -
Incentivized Research Data Sharing, Reusing, and Repurposing with Blockchain Technologies
Seneviratne, Oshani; McGuinness, Deborah L. (University of Hawaii at Manoa, 2022)Data sharing is very important for accelerating scientific research, business innovations, and for informing individuals. Yet, concerns over data privacy, cost, and lack of secure data-sharing solutions have prevented data ... -
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 ... -
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 ... -
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 ... -
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 ...