• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.17 no.4
• /
• pp.1080-1099
• /
• 2023

Digital healthcare combined with telemedicine services in the form of convergence with digital technology and AI is developing rapidly. Digital healthcare research is being conducted on many conditions including shock. However, the causes of shock are diverse, and the treatment is very complicated, requiring a high level of medical knowledge. In this paper, we propose a shock detection method based on the correlation between shock and data extracted from hemodynamic monitoring equipment. From the various parameters expressed by this equipment, four parameters closely related to patient shock were used as the input data for a machine learning model in order to detect the shock. Using the four parameters as input data, that is, feature values, a random forest-based ensemble machine learning model was constructed. The value of the mean arterial pressure was used as the correct answer value, the so called label value, to detect the patient's shock state. The performance was then compared with the decision tree and logistic regression model using a confusion matrix. The average accuracy of the random forest model was 92.80%, which shows superior performance compared to other models. We look forward to our work playing a role in helping medical staff by making recommendations for the diagnosis and treatment of complex and difficult cases of shock.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.4
• /
• pp.2060-2077
• /
• 2019

Recently, mobile healthcare services have attracted significant attention because of the emerging development and supply of diverse wearable devices. Smartwatches and health bands are the most common type of mobile-based wearable devices and their market size is increasing considerably. However, simple value comparisons based on accumulated data have revealed certain problems, such as the standardized nature of health management and the lack of personalized health management service models. The convergence of information technology (IT) and biotechnology (BT) has shifted the medical paradigm from continuous health management and disease prevention to the development of a system that can be used to provide ground-based medical services regardless of the user's location. Moreover, the IT-BT convergence has necessitated the development of lifestyle improvement models and services that utilize big data analysis and machine learning to provide mobile healthcare-based personal health management and disease prevention information. Users' health data, which are specific as they change over time, are collected by different means according to the users' lifestyle and surrounding circumstances. In this paper, we propose a prediction model of user physical activity that uses data characteristics-based long short-term memory (DC-LSTM) recurrent neural networks (RNNs). To provide personalized services, the characteristics and surrounding circumstances of data collectable from mobile host devices were considered in the selection of variables for the model. The data characteristics considered were ease of collection, which represents whether or not variables are collectable, and frequency of occurrence, which represents whether or not changes made to input values constitute significant variables in terms of activity. The variables selected for providing personalized services were activity, weather, temperature, mean daily temperature, humidity, UV, fine dust, asthma and lung disease probability index, skin disease probability index, cadence, travel distance, mean heart rate, and sleep hours. The selected variables were classified according to the data characteristics. To predict activity, an LSTM RNN was built that uses the classified variables as input data and learns the dynamic characteristics of time series data. LSTM RNNs resolve the vanishing gradient problem that occurs in existing RNNs. They are classified into three different types according to data characteristics and constructed through connections among the LSTMs. The constructed neural network learns training data and predicts user activity. To evaluate the proposed model, the root mean square error (RMSE) was used in the performance evaluation of the user physical activity prediction method for which an autoregressive integrated moving average (ARIMA) model, a convolutional neural network (CNN), and an RNN were used. The results show that the proposed DC-LSTM RNN method yields an excellent mean RMSE value of 0.616. The proposed method is used for predicting significant activity considering the surrounding circumstances and user status utilizing the existing standardized activity prediction services. It can also be used to predict user physical activity and provide personalized healthcare based on the data collectable from mobile host devices.

• Journal of Digital Convergence
• /
• v.11 no.4
• /
• pp.467-472
• /
• 2013

Recently, the value of ICT-based medical devices, equipments, software and service development are is increased according to strengthening the convergence among ICT, medical technologies and services. This paper presents the new convergence business models by applying cloud service to medical industry. In order to develop the new convergence business models, we checked the validity and feasibility through analyzing the medical market environments such as medical data backup, medical regulation etc. and present the new convergence business models and the direction of commercial business models for customer acquisition, market expansion and competitiveness improvement. This study is to provide the guidelines for establishing the core capacity strengthening strategy and partnership cooperation strategy when we design a new convergence business models in various industrial fields.

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.34 no.2
• /
• pp.59-92
• /
• 2023

The purpose of this study is to suggest ways to improve medical librarians' educational programs to improve domestic medical library user services. To this end, the role of medical librarians was investigated, and the education areas were itemized, and then the MLA in the US and the KMLA in Korea were compared and analyzed. As a result, the improvement points for medical librarian education programs in Korea are: First, expansion of certification programs that select various types of education programs, education areas, education contents, and specialized fields, collaboration programs with related institutions, and education programs that advocate the value of KMLA are required. Second, there is a need for various educational programs in the current educational areas, such as 'research support service' and 'education/education design/consultation'. In particular, it is necessary to provide 'consumer health information service' and 'disaster information service' for which there is no education at all. In addition, it is necessary to precede the establishment of regulations on the domestic medical librarian education curriculum for the education of various 'information services in the field related to medicine'. Third, it is necessary to provide online education contents for librarians who have difficulty participating in face-to-face education.

• Asian Pacific Journal of Cancer Prevention
• /
• v.17 no.6
• /
• pp.2995-2999
• /
• 2016

Background: Triple-negative breast cancer (TNBC) often presents as an interval cancer with short survival upon metastasis and thus represents an important clinical challenge. The present study investigated the clinicopathologic characteristics and long term survival outcome of early and locally advanced TNBC. Materials and Methods: Medical records were reviewed retrospectively for 148 consecutive confirmed cases of TNBC treated in a single unit at our centre. Demographic profile, tumor type, histopathology details, treatment and follow-up information was recorded and immunohistochemistry was performed. Results: Age group >50 years was associated with tumors of clinical stage 3 (53.8%), pathological stage 3 (46.2%), pathological grade 3 (45.7%), presence of extracapsular extension (ECE, 48.5%) and lymphovascular invasion (LVI, 64.9%). Locally advanced breast cancers (LABCs) were characterized by pathological stage 3 (96.2%), presence of ECE (100%) and absence of LVI (46.7%) as compared to early breast cancers (EBCs) which had higher incidence of lower stage tumors (100%), absence of ECE (82%) and presence of LVI (91.9%; p-value <0.001. Better relapse free survival was observed in patients with no axillary involvement (69%; p-value <0.001) and absence of ECE (64%; p-value <0.001). Improved overall survival was seen in patients with EBC (90%; p-value 0.008), clear axilla (86%; p-value <0.001), absence of ECE (87%; p-value <0.001) and negative lymph nodes (90%; p-value 0.006). Conclusions: TNBCs are aggressive tumors which show poor long term survival. Patients with TNBC benefit from chemotherapy, thus better and less toxic treatment options are needed. Identification of newer targets and development of targeted therapies are the need of the hour.

• Health Policy and Management
• /
• v.29 no.4
• /
• pp.445-453
• /
• 2019

Background: This study is to investigate the association between the distribution of multimorbidity and length of stay and medical expenses among inpatients in a municipal hospital to achieve an integrated care setting. Methods: We used the exploratory factor analysis and the generalized estimating equation model to analyze the data from patients living in the northeast region of Seoul, who were hospitalized from January 2017 to December 2017 in a municipal hospital. Results: As a result of the factor analysis, seven types of multiple chronic diseases were classified. Among the elderly patients admitted to municipal hospitals, the burden of medical expenses was mainly influenced by the length of stay (B=310,719, p-value <0.0001), not the type of disease (all not significant). Length of stay were mainly due to psychiatric illness (factor 1: B=4.323, p-value <0.0001) related to the brain and metabolic diseases (factor 2: B=2.364, p-value=0.003). Conclusion: This study showed that the medical expenses of the elderly patients were largely due to prolonged hospitalization, not multimorbidity. Therefore, it is necessary to develop an integrated care paradigm strategy cope with the multimorbidity of the elderly in the community and to alleviate the socio-economic burden.

• Journal of Korea Trade
• /
• v.25 no.1
• /
• pp.112-132
• /
• 2021

Purpose - This study aims to analyze the international marketing strategies of domestic medical institutions in the international medical market, and to determine whether such strategies increase international market share. With this approach, this study examines the impact of international marketing and social capital on international management performance through global competency and national image. It is hoped that this study can provide some insight on international marketing strategies. Design/methodology - In order to verify the research hypotheses, this study investigates medical institutions based in Incheon, Seoul, Gyeonggi Province, which provides medical services for foreigners. The target population is medical staff and interpreters in charge of administrative work, and a total of 194 copies were collected for 30 days. Of the collected questionnaires, a total of 171 copies were chosen for final analysis, excluding questionnaires with lack of information. Structural equations were used for analyzing the data by employing the R program. Findings - Our analysis suggests that international marketing and global competency performance have an effect on management performance. However, social capital appears to have no effect on global competency and management performance. Originality/value - Given the lack of research on international medical institutions, this study can be useful in the sense that it can help companies improve international marketing performance. Further, global competency was empirically proved to have a strong mediating effect that enhances total effect, while playing a mediating role between international marketing activities and management performance. This study is of great academic value in that it has comprehensively reviewed and systematized existing studies, and conducted empirical studies in the absence of domestic studies.

• The Journal of the Korea Contents Association
• /
• v.13 no.11
• /
• pp.807-814
• /
• 2013

Because there are growing demands for new information service of Korean medicine (KM) accommodated changes in the paradigm of health communication, we aimed to apply health 2.0 - which shares health information to improve individuals' health - extensively in KM. First we studied about the concepts and characteristics of health 2.0 and analyzed the pros and cons of KM information services. Finally we drew the KM health 2.0 framework from the analyzed results. KM health 2.0 framework is designed to raise the value of KM information through circulation of certified medical information to prevent medical accident. And it is also designed to integrate information through big data analysis technology from the information of individual services to recreate KM contents.

• Journal of the Optical Society of Korea
• /
• v.17 no.4
• /
• pp.328-335
• /
• 2013

Due to the rapid advancement of auto-refractor technology, most optometry shops provide refraction services. Despite their speed and convenience, the measurement values provided by auto-refractors include a significant degree of error due to psychological and physical factors. Therefore, there is a need for repetitive testing to obtain a smaller mean error value. However, even repetitive testing itself might not be sufficient to ensure accurate measurements. Therefore, research on a method of measurement that can complement auto-refractor measurements and provide confirmation of refraction results needs to be conducted. The customized optometry model described herein can satisfy the above requirements. With existing technologies, using human eye measurement devices to obtain relevant individual optical feature parameters is no longer difficult, and these parameters allow us to construct an optometry model for individual eyeballs. They also allow us to compute visual images produced from the optometry model using the CODE V macro programming language before recognizing the diffraction effects visual images with the neural network algorithm to obtain the accurate refractive diopter. This study attempts to combine the optometry model with the back-propagation neural network and achieve a double check recognition effect by complementing the auto-refractor. Results show that the accuracy achieved was above 98% and that this application could significantly enhance the service quality of refraction.

• The Korean Journal of Emergency Medical Services
• /
• v.27 no.2
• /
• pp.79-89
• /
• 2023

Purpose: This study aimed to develop a standardized protocol of systematic and explicit roles and procedures for paramedics for the maternal and newborn management during prehospital emergency delivery situations. Methods: This study is a methodological study with detailed step-by-step items proposed by an expert group based on evidence from a literature review. The content validity of the proposed preliminary prehospital emergency delivery protocol was verified before the final protocol was confirmed. Results: All 23 detailed items of the preliminary protocol met the reference cut-off (CVI value of 0.8 or higher). After considering, revising, and supplementing expert opinions for each of the 23 items 23 detailed in the proposed protocols, four steps were confirmed. The steps included five items for the management of the imminent mother, 10 items for delivery progress, five items for newborn management, and three items for postpartum management of the mother. Conclusion: This study's findings may serve as reference for developing future specialized training programs for paramedics, to ensure enhanced competence in prehospital emergency delivery situations. The protocol should be reviewed and revised periodically to ensure currency.