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Food for thought: A natural language processing analysis of the 2020 Dietary Guidelines publice comments.

The American journal of clinical nutrition Aug 2, 2021
BACKGROUND: The Administrative Procedure Act of 1946 guarantees the public an opportunity to view and comment on the 2020 Dietary Guidelines as part of the policymaking process. In the past, public comments were submitted by postal mail or public hea...
Natural Language Processing Food Nutrition Policy Humans Diet Social Media
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Why do people oppose mask wearing? A comprehensive analysis of U.S. tweets during the COVID-19 pandemic.

Journal of the American Medical Informatics Association : JAMIA Jul 14, 2021
OBJECTIVE: Facial masks are an essential personal protective measure to fight the COVID-19 (coronavirus disease) pandemic. However, the mask adoption rate in the United States is still less than optimal. This study aims to understand the beliefs held...
Public Opinion Humans Masks Machine Learning Attitude to Health United States COVID-19 Social Media
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Developing a standardized protocol for computational sentiment analysis research using health-related social media data.

Journal of the American Medical Informatics Association : JAMIA Jun 12, 2021
OBJECTIVE: Sentiment analysis is a popular tool for analyzing health-related social media content. However, existing studies exhibit numerous methodological issues and inconsistencies with respect to research design and results reporting, which could...
Machine Learning Natural Language Processing Humans Data Analysis Social Media Data Curation Attitude to Health
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Identifying HIV-related digital social influencers using an iterative deep learning approach.

AIDS (London, England) May 1, 2021
OBJECTIVES: Community popular opinion leaders have played a critical role in HIV prevention interventions. However, it is often difficult to identify these 'HIV influencers' who are qualified and willing to promote HIV campaigns, especially online, b...
Deep Learning HIV Infections United States Humans Social Media
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The risk of racial bias while tracking influenza-related content on social media using machine learning.

Journal of the American Medical Informatics Association : JAMIA Mar 18, 2021
OBJECTIVE: Machine learning is used to understand and track influenza-related content on social media. Because these systems are used at scale, they have the potential to adversely impact the people they are built to help. In this study, we explore t...
Influenza, Human Influenza Vaccines Datasets as Topic Support Vector Machine Social Media Black or African American Racism Humans Neural Networks, Computer Machine Learning
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Emergency department frequent user subgroups: Development of an empirical, theory-grounded definition using population health data and machine learning.

Families, systems & health : the journal of collaborative family healthcare Mar 1, 2021
Frequent emergency department (ED) use has been operationalized in research, clinical practice, and policy as number of visits to the ED, despite the fact that this definition lacks empirical evidence and theoretical foundation. To date, there are no...
Emergency Service, Hospital Patient Acceptance of Health Care Florida Grounded Theory Population Health Management Machine Learning Cluster Analysis Humans Social Media
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Applying natural language processing and machine learning techniques to patient experience feedback: a systematic review.

BMJ health & care informatics Mar 1, 2021
OBJECTIVES: Unstructured free-text patient feedback contains rich information, and analysing these data manually would require a lot of personnel resources which are not available in most healthcare organisations.To undertake a systematic review of t...
Bayes Theorem Patient Satisfaction Patient Outcome Assessment Feedback Social Media Natural Language Processing Machine Learning Electronic Health Records Humans
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Exploring the Influential Factors of Consumers' Willingness Toward Using COVID-19 Related Chatbots: An Empirical Study.

Medical archives (Sarajevo, Bosnia and Herzegovina) Feb 1, 2021
BACKGROUND: Consumers' willingness to use health chatbots can eventually determine if the adoption of health chatbots will succeed in delivering healthcare services for combating COVID-19. However, little research to date has empirically explored inf...
Attitude to Health Consumer Behavior Humans Social Perception Surveys and Questionnaires COVID-19 Artificial Intelligence Social Media Adult Telemedicine Male
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Application of unsupervised machine learning to identify and characterise hydroxychloroquine misinformation on Twitter.

The Lancet. Digital health Feb 1, 2021
Communication Social Media Unsupervised Machine Learning COVID-19 Drug Treatment Internet Use Hydroxychloroquine Quackery Humans Machine Learning
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The next-generation bots interfering with the US election.

Nature Nov 1, 2020
Politics Public Health Machine Learning Humans Artificial Intelligence Data Science COVID-19 United States Communication Russia Social Media China Computer Security
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