1,720,991 research outputs found
Efficient and Explainable Risk Assessments for Imminent Dementia in an Aging Cohort Study
No full textThis is the accepted manuscript version of the work published in its final form as Beebe-Wang, Nicasia; Okeson, Alex; Althoff, Tim; Lee, Su-In. IEEE Journal of Biomedical and Health Informatics 25(7). doi.org/10.1109/JBHI.2021.3059563
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Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Multimodal Models of Time Series and Text
No full textThesis (Ph.D.)--University of Washington, 2024Time series are critical data which drive countless decisions in finance, healthcare, and science. However, multimodal NLP research has mostly focused on images and video. Here I enumerate barriers towards such models and describe my work towards mitigating them. I detail new multimodal NLP tasks for reasoning about time series, describe an LLM-powered agent that can answer questions about time series, and present methods for pretraining time series encoders. I also share work on using language models for code generation to assist scientists
Human-AI Collaboration to Support Mental Health and Well-Being
No full textThesis (Ph.D.)--University of Washington, 2024As mental health conditions surge worldwide, healthcare systems are struggling to provide accessible and high-quality mental health care for all. Although therapy can support people struggling with mental health challenges, barriers like clinician shortages and mental health stigma commonly limit people's access to therapy. In this thesis, I study how human-AI collaboration can improve access to and quality of mental health support. First, I study how human-AI collaboration can empower people who provide support to conduct effective and high-quality conversations. Specifically, I focus on peer supporters on online peer support platforms like Reddit and TalkLife. While peer supporters are motivated and well-intentioned to help support seekers, they are typically untrained and unaware of key psychotherapy skills, such as empathy, that foster effective support. Using a reinforcement learning-based method, evaluated through a randomized trial with 300 peer supporters from the largest peer support platform, I demonstrate that AI-based feedback helps peer supporters express empathy more effectively in their conversations. Second, I investigate how human-AI collaboration can empower people who seek support by making self-guided mental health interventions more accessible and easier to engage with. Self-guided interventions, such as "do-it-yourself" tools to learn and practice coping skills, are often cognitively demanding and emotionally triggering, creating accessibility barriers that limit their wide-scale implementation and adoption. Using cognitive restructuring of negative thoughts as a case study, evaluated through a randomized trial on a large mental health website with 15,531 participants, I show that human-AI collaboration supports people in overcoming negative thoughts and informs psychology theory about processes that lead to positive outcomes. Third, I systematically evaluate human-AI collaboration systems used for mental health support. While there is great interest in utilizing AI for mental health support, there is a significant lack of methods to evaluate their effectiveness, quality, equity, and safety. I study how clinical trials can be conducted to effectively evaluate short-term and long-term outcomes, equity, and safety of AI-based mental health interventions comparing them to traditional approaches. Moreover, I develop a computational framework to automatically assess the behavior of large language models (LLM) when employed as therapists. By analyzing 13 different psychotherapy techniques, I compare the behavior of LLM therapists against that of high- and low-quality human therapy. My analysis reveals that LLMs often resemble behaviors more commonly exhibited in low-quality therapy rather than high-quality therapy, such as offering a higher degree of problem-solving advice when clients share emotions, which is against typical recommendations. My thesis develops two human-AI collaboration systems to support mental health and well-being, along with an evaluation framework for such systems. My work opens opportunities to improve the learning and practice of mental health strategies and coping skills for both support seekers and support providers through human-AI collaboration interventions
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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