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Full-Text Articles in Health Information Technology
A Smartwatch Step-Counting App For Older Adults: Development And Evaluation Study, George Boateng, Curtis L. Petersen, David Kotz, Karen L. Fortuna, Rebecca Masutani, John A. Batsis
A Smartwatch Step-Counting App For Older Adults: Development And Evaluation Study, George Boateng, Curtis L. Petersen, David Kotz, Karen L. Fortuna, Rebecca Masutani, John A. Batsis
Dartmouth Scholarship
Background: Older adults who engage in physical activity can reduce their risk of mobility impairment and disability. Short amounts of walking can improve quality of life, physical function, and cardiovascular health. Various programs have been implemented to encourage older adults to engage in physical activity, but sustaining their motivation continues to be a challenge. Ubiquitous devices, such as mobile phones and smartwatches, coupled with machine-learning algorithms, can potentially encourage older adults to be more physically active. Current algorithms that are deployed in consumer devices (eg, Fitbit) are proprietary, often are not tailored to the movements of older adults, and have …
Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston
Leveraging Context Patterns For Medical Entity Classification, Garrett Johnston
Computer Science Senior Theses
The ability of patients to understand health-related text is important for optimal health outcomes. A system that can automatically annotate medical entities could help patients better understand health-related text. Such a system would also accelerate manual data annotation for this low-resource domain as well as assist in down- stream medical NLP tasks such as finding textual similarity, identifying conflicting medical advice, and aspect-based sentiment analysis. In this work, we investigate a state-of-the-art entity set expansion model, BootstrapNet, for the task of medical entity classification on a new dataset of medical advice text. We also propose EP SBERT, a simple model …
The Feasibility And Utility Of Harnessing Digital Health To Understand Clinical Trajectories In Medication Treatment For Opioid Use Disorder: D-Tect Study Design And Methodological Considerations, Lisa A. Marsch, Ching-Hua Chen, Sara R. Adams, Asma Asyyed, Monique B. Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C. Jacobson, Heather K. Jones, David Kotz, Chantal A. Lambert-Harris, Zhiguo Li, Bethany Mcleman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Cynthia I. Campbell
The Feasibility And Utility Of Harnessing Digital Health To Understand Clinical Trajectories In Medication Treatment For Opioid Use Disorder: D-Tect Study Design And Methodological Considerations, Lisa A. Marsch, Ching-Hua Chen, Sara R. Adams, Asma Asyyed, Monique B. Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C. Jacobson, Heather K. Jones, David Kotz, Chantal A. Lambert-Harris, Zhiguo Li, Bethany Mcleman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Cynthia I. Campbell
Dartmouth Scholarship
Introduction: Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substance use during substance use disorder treatment. However, much of this literature has examined a small set of potential moderators or mediators of outcomes in MOUD treatment and may lead to over-simplified accounts of treatment non-adherence. Digital health methodologies offer great promise for capturing intensive, longitudinal ecologically-valid …