Digital Health Care Industry Ecosystem: Network Analysis

Park, Yoonseo; Park, Sewon; Lee, Munjae

doi:10.2196/37622

Cited by 9 publications

(8 citation statements)

References 38 publications

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“…To measure the effectiveness, the survey subjects were classified according to whether or not they had the usage experience of the public health center, and then among the local residents using the health centers, the subjects were divided and verified according to whether to have used the data-linked service. 32 …”

Section: Discussionmentioning

confidence: 99%

Analyzing the Effectiveness of Data-Linked Projects for Health Promotion in Public Health Centers of South Korea

Yoon¹,

Kim²,

Choi³

et al. 2023

RMHP

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Purpose The purpose of this study lies in verifying the effectiveness of the health promotion project which the public health center at the local level conducted by systematically linking the health examination results from the Health Insurance Corporation. We intend to emphasize the importance of linking the health-related public data. Methods A survey was conducted to measure the effect of improving health behavior using EQ-5D-5L and demographic variables. Results As a result of the analysis, the residents (3.13) who had experienced the use of public health centers recognized more necessity for the service linked systematically with health checkup data than those (2.93) who had not. In addition, the residents who had experienced the use of public health centers responded that their chronic diseases had improved compared to a year ago (2.78→2.93). Next, those (3.04) who had experienced the services linked with health checkup data recognized that their chronic diseases and health conditions had been improved compared to those (2.81) who had not. However, in EQ-5D-5L, after using the service, mobility showed no difference between those who had used the service and those who had not. Furthermore, even in terms of self-management, daily life, etc., the management ability was further improved compared to those who had not used it, before using the service. Conclusion This study showed the improved health level when the health promotion service of the public health center was provided by systematically linking the health checkup data of the Health Insurance Corporation in Korea. In order to increase the effectiveness of health data-linked projects, it is necessary to prepare guidelines for linking the public health data and to expand the data-linked project. It will be needed to further subdivide the health checkup results to provide customized services, and to secure dedicated personnel to reinforce the system link.

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Section: Discussionmentioning

confidence: 99%

Analyzing the Effectiveness of Data-Linked Projects for Health Promotion in Public Health Centers of South Korea

Yoon¹,

Kim²,

Choi³

et al. 2023

RMHP

Self Cite

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“…DALL-E 2’s powerful generative capabilities raise the question of whether these can be transferred to the medical domain to create or augment data, as medical data can be sparse and hard to come by [ 9 , 10 ]. Given the large number of images on which DALL-E 2 was trained, it is reasonable to assume that the training data for DALL-E 2 included radiological images and that the model may have learned something about the composition and structure of x-ray, cross-sectional, and ultrasound images.…”

Section: The Potential Impact Of Generative Models In Radiologymentioning

confidence: 99%

What Does DALL-E 2 Know About Radiology?

Adams¹,

Busch²,

Truhn³

et al. 2023

J Med Internet Res

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Generative models, such as DALL-E 2 (OpenAI), could represent promising future tools for image generation, augmentation, and manipulation for artificial intelligence research in radiology, provided that these models have sufficient medical domain knowledge. Herein, we show that DALL-E 2 has learned relevant representations of x-ray images, with promising capabilities in terms of zero-shot text-to-image generation of new images, the continuation of an image beyond its original boundaries, and the removal of elements; however, its capabilities for the generation of images with pathological abnormalities (eg, tumors, fractures, and inflammation) or computed tomography, magnetic resonance imaging, or ultrasound images are still limited. The use of generative models for augmenting and generating radiological data thus seems feasible, even if the further fine-tuning and adaptation of these models to their respective domains are required first.

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“…Moreover, there is a limit to identifying the practical issues of fitness centers due to COVID-19 using only research based on surveys or interviews conducted with convenient participant samples. By contrast, investigations through mass media reports have the advantage of grasping the general perception of the public on issues and social agenda [8], and despite the recent increase in studies using big data to analyze health issues related to COVID-19 [9][10][11], research in the fitness center industry remains very limited.…”

Section: Studies On Fitness Centers During Covid-19mentioning

confidence: 99%

“…Accordingly, the number of studies using big data (e.g., press reports and articles, social media) to analyze health issues related to COVID-19 has increased recently. For example, recent studies investigated issues in the digital healthcare industry through network analysis [9], major issues in news articles related to health communication [10], and COVID-19-related stress factors [11]. However, to our knowledge, no studies have investigated trends or issues considering a general discussion of society using big data analysis based on topics related to fitness centers, which are facing a crisis due to the COVID-19 pandemic.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Issues in Fitness Centers through News Articles before and after the COVID-19 Pandemic in South Korea: Applying Big Data Analysis

2023

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This study aimed to identify major topics and trends of media reports in news articles related to fitness centers before and after COVID-19 using big data analysis and to suggest future improvements. We collected 20,528 news articles from 2018 to 2019 (pre-COVID-19) and 20,264 news articles from 2020 to 2021 (post-COVID-19) and conducted frequency analysis, topic modeling, and sentiment analysis. The top keywords related to fitness centers were fitness, health, healthcare, and center both before and after COVID-19, but after the outbreak of COVID-19, new keywords emerged, such as digital, COVID-19, indoor, confirmed, platform, and mobile. Since the COVID-19 pandemic, four topics were extracted: COVID-19 and Exercise, Digital Smart Health Care, Health and Beauty, and Indoor Sports Facilities and Quarantine. Sentiment analysis showed that the frequency of negative words increased by approximately three times since the COVID-19 pandemic. Due to COVID-19, the top keywords of the negative data in order were infection, virus, disease, and limit. Based on the identified major issues and trends related to the fitness industry, these results can be used as foundational data for the future planning and policy development of the fitness industry.

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Digital Health Care Industry Ecosystem: Network Analysis

Cited by 9 publications

References 38 publications

Analyzing the Effectiveness of Data-Linked Projects for Health Promotion in Public Health Centers of South Korea

Analyzing the Effectiveness of Data-Linked Projects for Health Promotion in Public Health Centers of South Korea

What Does DALL-E 2 Know About Radiology?

Analysis of Issues in Fitness Centers through News Articles before and after the COVID-19 Pandemic in South Korea: Applying Big Data Analysis

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