• Journal of Digital Contents Society
• /
• v.16 no.1
• /
• pp.85-96
• /
• 2015

With the emergence of smart media and devices which are able to continuous data monitor, the usage patterns of access and acquire health information are changed. Health contents should be provided to promote intrinsic motivation considering the way of cognizing and processing data in human information interaction. For this, planning for prevention centered health contents is required to utilize personal information and medical big data for engagement with the contents. Therefore, this paper reviews previous studies of health communication dealing with users' information literacy like e-health literacy. In addition, the paper classifies ways of communication when mediate IT as immediacy, interaction and data capturing. In conclusion, strategies of health contents for promoting users' intrinsic motivation are explored and its implications are discussed.

• Neurospine
• /
• v.15 no.4
• /
• pp.329-337
• /
• 2018

Objective: Machine learning algorithms excel at leveraging big data to identify complex patterns that can be used to aid in clinical decision-making. The objective of this study is to demonstrate the performance of machine learning models in predicting postoperative complications following anterior cervical discectomy and fusion (ACDF). Methods: Artificial neural network (ANN), logistic regression (LR), support vector machine (SVM), and random forest decision tree (RF) models were trained on a multicenter data set of patients undergoing ACDF to predict surgical complications based on readily available patient data. Following training, these models were compared to the predictive capability of American Society of Anesthesiologists (ASA) physical status classification. Results: A total of 20,879 patients were identified as having undergone ACDF. Following exclusion criteria, patients were divided into 14,615 patients for training and 6,264 for testing data sets. ANN and LR consistently outperformed ASA physical status classification in predicting every complication (p < 0.05). The ANN outperformed LR in predicting venous thromboembolism, wound complication, and mortality (p < 0.05). The SVM and RF models were no better than random chance at predicting any of the postoperative complications (p < 0.05). Conclusion: ANN and LR algorithms outperform ASA physical status classification for predicting individual postoperative complications. Additionally, neural networks have greater sensitivity than LR when predicting mortality and wound complications. With the growing size of medical data, the training of machine learning on these large datasets promises to improve risk prognostication, with the ability of continuously learning making them excellent tools in complex clinical scenarios.

• Journal of the Korean Society of Radiology
• /
• v.16 no.3
• /
• pp.225-231
• /
• 2022

Transcendence of space and time, virtual reality, augmented reality, etc. are being realized through the latest technologies in the era of the 4th industrial revolution. In a situation where they are currently experiencing artificial intelligence, augmented reality, big data, etc., the degree of interest in the latest technologies of the 4th industrial revolution for radiology students, the necessary competencies in the 4th industrial revolution era, and the prospect of the radiation field employment environment in the 4th industrial revolution era The purpose of this study was to find out the level of awareness of From February 7th to February 18th, 2022, surveys on awareness were analyzed using questionnaires for 2nd and 3rd year students in the Department of Radiology at S University in Daegu. As a result of the study, the level of interest in 3D modeling was shown to be the highest with an average of 3.34 ± 1.09 points, and interest in big data and artificial intelligence was also shown with an average of 3.27 ± 1.17 and 3.33 ± 1.07 points. In addition, the correlation between the awareness of the necessary competencies in the 4th industrial revolution era and the awareness of the prospects for employment in the radiation field in the 4th industrial revolution era was the highest (r=0.778, p<0.01), and the interest in the latest technologies in the 4th industrial revolution and the 4th industrial revolution It was found that there was also a correlation between the perceptions of the necessary capabilities of the times (r=0.694, p<0.01). In the era of the 4th industrial revolution, it is judged that it is necessary to strengthen professional education that can handle the latest technologies such as 3D printing, artificial intelligence, and big data, and to strengthen employment capabilities related to the latest technologies in the field of radiation medical technology.

• Journal of Convergence for Information Technology
• /
• v.9 no.4
• /
• pp.1-7
• /
• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• Journal of Industrial Convergence
• /
• v.20 no.1
• /
• pp.87-96
• /
• 2022

This study aims to understand the actual conditions of adolescents with allergic diseases and factors related to mental health. It is intended to provide basic data for disease management. As for the research method, big data of the 16th Youth Health Behavior Survey were analyzed secondary, and x²-test was used using the SPSS 25 program8, odds ratio and 95% confidence interval were calculated to determine the degree of association, and multi-logistic regression analysis was performed. Studies have shown that 37.1% of adolescents with allergic diseases have stress perception, 27.6% of depression experience rate and 12.5% of suicidal thoughts, and the likelihood of stress perception, depression experience, and suicidal thoughts among adolescents with allergic diseases was higher. As a result of this study, it was found that the presence or absence of allergic diseases in adolescents has a significant effect on mental health, and we intend to use it as basic data for prevention and research on diseases that can lead to mental illness and adolescent mental health.

• Journal of Industrial Convergence
• /
• v.22 no.2
• /
• pp.97-103
• /
• 2024

The purpose of this study was to examine the impact of balance training on the Inbody and recovery of the balance capability in stroke patient with obesity. The exercise program was to conduct obesity group and normal weight group, 22 subjects were divided equally into experimental(obesity) and controlled group(normal weight), assigned to excercise using the balance training system for 30min a day and 5 days a week. Every pre and post-experimental data of both groups were gathered by Inbody and BSS(Biodex Medical Systems) for 8 weeks. As a result, Comparing the intra-group data measured by Inbody, obesity group showed significant difference in every parameter (p<.05). In the inter-group data, every parameter showed significant difference between both groups (p<.05). Comparing the intra-group data of LOS(Limits Of Stability), obesity group showed significant difference with all parameters, except with 'Backward' and 'Left' (p<.05). In the inter-group data, 'Forward' parameter showed significant difference. Comparing the intra-group data of PS(Postural Stability), obesity group showed significant difference with all parameters (p<.05). The inter-group PS(Postural Stability) results differed significantly only with 'Med/lat'(p=.000). The above results implicate about the following conclusions that the balance training had a big effect on the Inbody and recovery of the balance capability in stroke patient with obesity.

• The Journal of the Korea Contents Association
• /
• v.20 no.5
• /
• pp.448-456
• /
• 2020

In the era of the Fourth Industrial Revolution, how well the explosive information and data are handled and used is recognized as a problem directly related to the competitiveness of the industry. In particular, the introduction of artificial intelligence technology in the medical field can be said to have a great social impact on its use, and this research was conducted to understand the trends of artificial intelligence according to the range of use case. In this study, the application of artificial intelligence in the healthcare field is divided into four scopes, (1) hospital solutions, (2) personal health care, (3) insurance, and (4) new drug development. Based on various cases and trends in artificial intelligence technology, this study tried to give directions on how to develop artificial intelligence in Korea. In this study, we wanted to find out the use cases of artificial intelligence in various areas of healthcare industry and describe the latest issues in healthcare to help the overall medical industry. The development of artificial intelligence-based medical systems has made it easier to manage the chronic patients, increased the accuracy of cancer or disease diagnosis, and helped developing new drugs faster and more efficiently. Through this study, the medical industry we wanted to give a direction to the future development of artificial intelligence in Korea.

• Journal of Korean society of Dental Hygiene
• /
• v.17 no.5
• /
• pp.921-930
• /
• 2017

Objectives: The purposes of this study were to analyze the trade newspapers related to 'recognition of the dental hygienist as the healthcare professional' using R program and to identify opinions of groups concerned with dental hygienists. Methods: This study was designed with contents analysis and cross-sectional. The subjects of the study were the articles for the last three years in medical and dental newspapers about the recognition of the dental hygienist as the healthcare professional. The collected articles were categorized and classified for each group's opinions about the issue. The key words were extracted according to the priorities of the opinions of agreement and disagreement. They were visualized after frequency analysis using R, a big data analysis program. Results: A total of 237 newspaper articles were extracted among 270 ones containing opinions. 245 were positive opinions and 25 were negatives. The main key words of the agreement were 'Amendment of Medical Law', 'Medical Practice', and 'Legal Guarantee of the Practice'. Advocates addressed that the issues should be resolved with the amendment of the law, as dental hygienists are not guaranteed to work based on the current law although they are actually doing the medical practices. Main key words of disagreement were 'Legal Guarantee of the Practice', 'Revision of Medical Technician Law', and 'Review of Job Type'. They described that the problem can be resolved by revising medical technicians act, and it needs to consider as job types of all healthcare professional. Conclusions: In the group who showed the positive opinions, it is possible to utilize measures such as promoting the cooperation of dental hygienists and developing public consensus through publicity.

• Health Policy and Management
• /
• v.25 no.4
• /
• pp.253-255
• /
• 2015

The concept of precision medicine-prevention and treatment strategies that take individual variability into account-is hot issue of US in the year 2015. Precision medicine is a new concept that approach patients individually by there characteristics, such as genome, life style, environmental exposure, etc. For developing the precision medicine, National Institute of Health of US has been prepared the Precision Medicine Initiative Cohort Program, at least 1 million people cohort. The US President Obama announced the Precision Medicine Initiative on 30th January 2015. He announced that he will pioneer a new model of patient-powered research that promises to accelerate biomedical discoveries and provide clinicians with new tools, knowledge, and therapies to select which treatments will work best for which patients. Most medical treatments have been designed for the 'average patient.' As a result of this 'one-size-fits-all-approach,' treatments can be very successful for some patients but not for others. This is changing with the emergence of precision medicine, an innovative approach to disease prevention and treatment that takes into account individual differences in people's genes, environments, and lifestyles. Precision medicine gives clinicians tools to better understand the complex mechanisms underlying a patient's health, disease, or condition, and to better predict which treatments will be most effective. The healthcare researcher should prepare the new medicine era such as bio-information technology convergence, big data study.

• Journal of Korean Academy of Nursing Administration
• /
• v.22 no.1
• /
• pp.67-79
• /
• 2016

Purpose: To develop strategies for research and development (R&D) in nursing service based on the policy direction of government supported R&D in Korea. Methods: This was a descriptive study to develop strategies for promoting R&D in nursing by analyzing investment trends and status quo, policy directions, and implementation of the details of government supported R&D through government reports, websites of relevant agencies and literature reviews. Results: Few nursing experts participated in clinical research on overcoming major diseases and in R&D for well-being and care. Development of nursing topics that meet the direction of government supported R&D were lacking. Insufficient implementation of nursing service R&D in a timely manner equipped with a performance-based system. Few research studies in R&D projects that included research using big data or contributing to developing medical instruments. Finally, an insufficient number of nursing specialists participated on government R&D advisory committees. Conclusion: For nursing service R&D development efforts should be toward quantitative expansion and qualitative improvements by sensitively recognizing policy direction of government supported R&D. The promotional capacity of nursing service R&D must be reinforced through a multidisciplinary approach and collaborative association with other professionals and the inclusion of nurse specialists on government R&D advisory committees.