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1.
Sport in Society: Cultures, Commerce, Media, Politics ; 26(3):390-408, 2023.
Article in English | CAB Abstracts | ID: covidwho-20237923

ABSTRACT

Opportunities to participate in physical activities (PA) and fitness exercises in public and private facilities have been reduced or banned due to social distancing regulations during the height of the global pandemic. Though Korea has not experienced lockdown, several venues have been restricted to prevent the spread of Covid-19. Despite the limitations of PA engagement, people have found alternative activities by using online platforms to keep active and fit. Thus, this study focuses on analyzing fitness-related video titles from YouTube. By collecting data through text mining and conducting network analysis, it provides basic knowledge of the fitness trends from pre- and post-Covid-19. As a result, 'exercise' was found to have the highest tendency and had strong connections to keywords that indicated specific methods of working out to become fit, but it also had connections to trendy keywords such as 'hip-up' and 'body-profile' which reflect the fitness culture in Korea.

2.
Sport in Society ; 26(3):390-408, 2023.
Article in English | ProQuest Central | ID: covidwho-2316079

ABSTRACT

Opportunities to participate in physical activities (PA) and fitness exercises in public and private facilities have been reduced or banned due to social distancing regulations during the height of the global pandemic. Though Korea has not experienced lockdown, several venues have been restricted to prevent the spread of Covid-19. Despite the limitations of PA engagement, people have found alternative activities by using online platforms to keep active and fit. Thus, this study focuses on analyzing fitness-related video titles from YouTube. By collecting data through text mining and conducting network analysis, it provides basic knowledge of the fitness trends from pre- and post-Covid-19. As a result, ‘exercise' was found to have the highest tendency and had strong connections to keywords that indicated specific methods of working out to become fit, but it also had connections to trendy keywords such as ‘hip-up' and ‘body-profile' which reflect the fitness culture in Korea.

3.
Int J Med Inform ; 170: 104956, 2023 02.
Article in English | MEDLINE | ID: covidwho-2149862

ABSTRACT

BACKGROUND: Owing to the prevalence of the coronavirus disease (COVID-19), coping with clinical issues at the individual level has become important to the healthcare system. Accordingly, precise initiation of treatment after a hospital visit is required for expedited processes and effective diagnoses of outpatients. To achieve this, artificial intelligence in medical natural language processing (NLP), such as a healthcare chatbot or a clinical decision support system, can be suitable tools for an advanced clinical system. Furthermore, support for decisions on the medical specialty from the initial visit can be helpful. MATERIALS AND METHODS: In this study, we propose a medical specialty prediction model from patient-side medical question text based on pre-trained bidirectional encoder representations from transformers (BERT). The dataset comprised pairs of medical question texts and labeled specialties scraped from a website for the medical question-and-answer service. The model was fine-tuned for predicting the required medical specialty labels among 27 labels from medical question texts. To demonstrate the feasibility, we conducted experiments on a real-world dataset and elaborately evaluated the predictive performance compared with four deep learning NLP models through cross-validation and test set evaluation. RESULTS: The proposed model showed improved performance compared with competitive models in terms of overall specialties. In addition, we demonstrate the usefulness of the proposed model by performing case studies for visualization applications. CONCLUSION: The proposed model can benefit hospital patient management and reasonable recommendations for specialties for patients.


Subject(s)
COVID-19 , Medicine , Humans , Artificial Intelligence , Adaptation, Psychological , Cognition , Natural Language Processing
4.
Sport in Society ; : 1-19, 2022.
Article in English | Taylor & Francis | ID: covidwho-2070030
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