A5083093819- Artificial Intelligence in Healthcare and Education
- Pharmaceutical industry and healthcare
- Rhetoric and Communication Studies
- Ethics in Clinical Research
- Climate Change Communication and Perception
- Pharmaceutical Economics and Policy
- Discourse Analysis in Language Studies
- Empathy and Medical Education
- Ethics and Social Impacts of AI
- Opioid Use Disorder Treatment
- Topic Modeling
- Machine Learning in Healthcare
- Health Policy Implementation Science
- Misinformation and Its Impacts
- scientometrics and bibliometrics research
- Healthcare cost, quality, practices
- Academic Publishing and Open Access
- Biomedical Text Mining and Ontologies
- Historical and Scientific Studies
- Pain Management and Placebo Effect
- Ethics in medical practice
- Semantic Web and Ontologies
- Explainable Artificial Intelligence (XAI)
- Interdisciplinary Research and Collaboration
- Law in Society and Culture
The University of Texas at Austin
2019-2025
University of British Columbia
2024
Council of Science Editors
2024
University of Wisconsin–Milwaukee
2012-2019
NHS Tayside
2019
York University
2018
Laryngograph (United Kingdom)
2013-2017
University of Kentucky
2016
University of Aberdeen
2014-2016
Council of Economic Advisers
2013
Background Large language models (LLMs) have the potential to support promising new applications in health informatics. However, practical data on sample size considerations for fine-tuning LLMs perform specific tasks biomedical and policy contexts are lacking. Objective This study aims evaluate selection techniques improved named entity recognition (NER) a custom set of conflicts interest disclosure statements. Methods A random 200 statements was prepared annotation. All “PERSON” “ORG”...
This Methodologies and Approaches piece argues artificially intelligent machine learning systems can be used to effectively advance justice-oriented research in technical professional communication (TPC). Using a preexisting dataset investigating patient marginalization pharmaceuticals policy discourse, we built tested 49 designed identify track rhetorical features of interest. Three popular one new approach feature engineering (text quantification) were evaluated. The results indicate that...
Recent agency scholarship has provided compelling accounts of how individuals can strategically occupy authoritative positions, in order to instantiate change. This article explores the discursive mechanisms this type legitimization disease. Drawing on ethnographic research, investigates a non-human agent (brain scans) contributed fibromyalgia's acceptance within highly regulated discourses western biomedicine.
This article pilots a study in statistical genre analysis, mixed-method approach for (a) identifying conventional responses as distribution within big data set and (b) assessing which deviations from the might be more effective changes audience, purpose, or context. The assesses pharmaceutical sponsor presentations at Food Drug Administration (FDA) drug advisory committee meetings. Preliminary findings indicate need to FDA conflict-of-interest policies.
This article uses data obtained from a 2-year study—observation, survey, written- and verbal-artifact analysis, interviews—of an interdisciplinary organization of pain management professionals to illustrate the analytic advantages Mol Latour's multiple-ontologies theories over incommensurability theory in understanding practice. We demonstrate that science medicine encompass variety practices transcend disciplinary boundaries ways not accounted for with theory. After explicating multiple...
It has been difficult historically for physicians, patients, and philosophers alike to quantify pain given that is commonly understood as an individual subjective experience. The process of measuring diagnosing often a fraught complicated process. New developments in diagnostic technologies assisted by artificial intelligence promise more accurate efficient diagnosis but these tools are known reproduce further entrench existing issues within the healthcare system, such poor patient treatment...
The goal of this study is to develop and validate a lightweight, interpretable machine learning (ML) classifier identify opioid overdoses in emergency medical services (EMS) records. We conducted comparative assessment three feature engineering approaches designed for use with unstructured narrative data. Opioid overdose annotations were provided by two harm reduction paramedics supporting annotators trained reliably match expert annotations. Candidate techniques included term...
Recent research in rhetoric of health and medicine (RHM) has worked to evaluate the effectiveness patient inclusion initiatives policy decision-making. Extending this line research, article evaluates extent which U.S. Food Drug Administration's (FDA) consumer representative programs meaningfully engage experiences. In so doing, study provides directed summative content analyses pharmaceuticals deliberation at 163 FDA drug advisory committee meetings. The results indicate that current...
Many expected federal public health agencies to provide timely and accurate information about the COVID-19 pandemic. That did not happen. In response, physicians epidemiologists have explored new ways educate protect against misinformation. One genre that has received significant uptake is tweetorial, threaded tweets followers on technical matters. This article builds prior studies of tweetorial explore how #MedTwitter #EpiTwitter communities refashioned emerging conventions as part efforts from
In British Columbia (BC) and across the territories of over 200 First Nations 39 Métis Nation Chartered communities, COVID-19 pandemic catalyzed a group partner organizations to rapidly establish seven virtual care pathways under Real-Time Virtual Support (RTVS) network. They aimed address inequitable access multiple barriers healthcare faced by rural, remote, Indigenous provide pan-provincial services. Mixed-method evaluation assessed implementation, patient provider experience, quality...
Effectively addressing wicked health problems, that is, those arising from complex multifactorial biological and socio-economic causes, requires transdisciplinary action. However, a significant body of research points toward substantial difficulties in cultivating collaboration. Accordingly, this article presents the results study adapts Systems Ethnography Qualitative Modeling (SEQM) response to problems. SEQM protocols were designed catalyze responses national defense concerns. We adapted...
This study demonstrates that NVivo, a popular research tool for content analysis, produces biased Cohen's kappa as it calculates the reliability statistic at character level, which is unsuitable most content-analytic studies adopting higher unit of analysis (e.g., sentence, paragraph). Based on empirical data and statistical simulation, this proposes method bias correction applicable to situations where two independent raters conduct binary coding.
Recently, scholars of new media have been exploring the relationships between genre theory and media. While these provided a great deal insight into nature e-genres how they function in professional contexts, few address relationship new-media theories from designer's perspective. This article presents results an ethnographic-style case study practice designer. These (a) confirm role dynamic rhetorical situations hybridity during design process; (b) suggest that current underestimate...
On October 22, 2012, six scientists and one civil servant were convicted of manslaughter for failing to properly warn the people L’Aquila, Italy, an impending earthquake that resulted in over 300 deaths 1,500 injuries. This article investigates a key event leading up this conviction: An emergency meeting scientists, servants, politicians determine whether or not advanced warning should be issued residents L’Aquila. The following investigation uses functional stasis analysis identify primary...
This study evaluates associations between aggregate conflicts of interest (COI) and drug safety. We used a machine-learning system to extract classify COI from PubMed-indexed disclosure statements. Individual were classified as Type 1 (personal fees, travel, board memberships, non-financial support), 2 (grants research or 3 (stock ownership industry employment). aggregated by type compared adverse events product. are associated with 1.1-1.8% increase in the number events, serious...