• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.157-160
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• 2004

The paper's suggestion is about hereditary facts between family members. Diagnosing patients from the point of patients temporary conditions, and so performing primitive examinations and treatments, can lead not only to frequent wrong diagnoses, and to huge medical expenses and times to the patients, but even to critical situation of patients or taking lives away. As a means to cut these cases down to a minimum, sharing medical treatment information between family members is suggested. This approach makes possible understanding physical constitution and environment between family members, and can result in bringing a faster treatment effect if some family member suffers from a similar disease. This approach, since a participation in a family membership effectuates all of family members, can minimize the membership fees, thus enabling inter-family health care on a home doctor basis.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1496-1506
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• 2020

With the progress of miniaturization and high performance of various sensors, a lot of data is generated in various fields and being collected in real-time, but the use of such large-capacity data is often unable to keep up with the collection technology. In the medical field, health data is collected and managed by platform, which causes inconvenience to users in searching their own health data and receiving medical services. In this paper, in order to solve these problems, we designed and implemented PHDItemReader to improve the speed of data query in a batch application environment that can integrate and process health data having various data expression formats. The experiment compared and analyzed 3 types of query speed based on 1,000,000 hypothetical health data, and as a result of the experiment, it was verified that the PHDItemReader implemented in this paper improved up to about 21% compared to the existing one.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.92-103
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• 2021

With the continuous acceleration of economic and social development, people gradually pay attention to their health, improve their living environment, diet, strengthen exercise, and even conduct regular health examination, to ensure that they always understand the health status. Even so, people still face many health problems, and the number of chronic diseases is increasing. Recently, COVID-19 has also reminded people that public health problems are also facing severe challenges. With the development of artificial intelligence equipment and technology, medical diagnosis expert systems based on big data have become a topic of concern to many researchers. At present, there are many algorithms that can help computers initially diagnose diseases for patients, but they want to improve the accuracy of diagnosis. And taking into account the pathology that varies from person to person, the health diagnosis expert system urgently needs a new algorithm to improve accuracy. Through the understanding of classic algorithms, this paper has optimized it, and finally proved through experiments that the combined classification algorithm improved by latent factors can meet the needs of medical intelligent diagnosis.

• Journal of Preventive Medicine and Public Health
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• v.48 no.4
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• pp.203-215
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• 2015

Objectives: This study was performed to investigate the relationship between the incidence of national notifiable infectious diseases (NNIDs) and meteorological factors, air pollution levels, and hospital resources in Korea. Methods: We collected and stored 660 000 pieces of publicly available data associated with infectious diseases from public data portals and the Diseases Web Statistics System of Korea. We analyzed correlations between the monthly incidence of these diseases and monthly average temperatures and monthly average relative humidity, as well as vaccination rates, number of hospitals, and number of hospital beds by district in Seoul. Results: Of the 34 NNIDs, malaria showed the most significant correlation with temperature (r=0.949, p<0.01) and concentration of nitrogen dioxide (r=-0.884, p<0.01). We also found a strong correlation between the incidence of NNIDs and the number of hospital beds in 25 districts in Seoul (r=0.606, p<0.01). In particular, Geumcheon-gu was found to have the lowest incidence rate of NNIDs and the highest number of hospital beds per patient. Conclusions: In this study, we conducted a correlational analysis of public data from Korean government portals that can be used as parameters to forecast the spread of outbreaks.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.271-274
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• 2018

More than 80% of the deaths in Korea are due to chronic diseases. Mobile applications continue to emerge where IT companies and medical hospitals work together to manage chronic diseases. In recent years, the development of artificial intelligence chatbot has been under way to improve the efficiency and convenience of management. Since the chatbot process the conversation by a dialogue, users who are familiar with the GUI-based environment may not be familiar with accessibility or usage. In this paper, we analyze UI / UX of the mobile application that manages diabetes in chronic diseases, and present the UI / UX design of chatbot through this result.

• Journal of the Korea Convergence Society
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• v.9 no.8
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• pp.355-363
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• 2018

This study is to provide insights for developing strategies and policy of MICE industry in Korea. Identifying current global statuses, trends, characteristics and analysing the strategic opinions of MICE experts', some strategies and policies were driven, which to activate MICE industry. Compared to Korea, America has comparative advantages in the size and configurations of MICE infrastructure. In order to get competitive edge, Korea needs to utilize various fused contents and stories of K-Series in MICE industry. Unique Venue and MICE destination development, which provide special experiences during the MICE participation, family friendly and children education oriented MICE environment policies are needed. Also, providing fun and Entertainment for MICE participants, demand for 'Green MICE' and medical tourism for the participants should be counted in developing strategic MICE policies.

• Journal of the Korea Convergence Society
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• v.9 no.6
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• pp.1-7
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• 2018

As IT technology develops recently, medical equipment used in hospitals is demanding high performance. However, since the user visits different hospitals depending on the user's situation, the medical information treated at the hospital is distributed among the hospitals. In this paper, we propose a model to efficiently integrate the health care information of the users stored in the hospital in order to collect the healthcare information of the users who visited the different hospitals. The proposed model synchronizes users' healthcare information collected from personal wearable devices to collect user - centered healthcare information. In addition, the proposed model performs integrity and validity check related to user's healthcare information in a database existing in a cloud environment in order to smoothly share data with the healthcare service center. In particular, the proposed model enables tree - based data processing to smoothly manage healthcare information collected from mobile platforms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.279-282
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• 2022

Acute lymphoblastic leukemia is an acute leukemia caused by suppression of bone marrow function due to overgrowth of immature lymphocytes in the bone marrow. It accounts for 30% of acute leukemia in adults, and children show a cure rate of over 80% with chemotherapy, while adults show a low survival rate of 20% to 50%. However, research on a machine learning algorithm based on medical image data for the diagnosis of acute lymphoblastic leukemia is in the initial stage. In this paper, we compare and analyze CNN algorithm models for quick and accurate diagnosis. Using four models, an experimental environment for comparative analysis of acute lymphoblastic leukemia diagnostic models was established, and the algorithm with the best accuracy was selected for the given medical image data. According to the experimental results, among the four CNN models, the InceptionV3 model showed the best performance with an accuracy of 98.9%.

• The Journal of the Convergence on Culture Technology
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• v.5 no.4
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• pp.203-208
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• 2019

Medical color graphic research will serve as the basis for globally expanding and disseminating the design quality of the company's products through the era of production of medical robots. This study was based on technologies and contents suitable for the era of medical robot bed expansion, universal medical color application, ergonomic color, etc. In addition, the medical bed robot's color research direction was presented from the perspective of universal design. Accordingly, a universal color design was proposed, taking the functions of a medical robot under development by a domestic company as an example. The characteristics of this robot bed can be divided into three types of functions: first, treatment characteristics for prevention of pressure ulcers with curative, second, automatic seat exchange with cleanliness for medical environment, and third, Convenient, which can implement patient transport. The main idea is to present a combination of functional colors appropriate for this. The resulting color analysis and universal color design techniques could be a useful methodology for illustrating the appearance and function of a modern medical robot bed.

• Journal of Convergence for Information Technology
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• v.10 no.6
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• pp.35-40
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• 2020

As we enter the society of the future, efforts to increase healthy living are a major area of concern for modern people. In particular, the development of technology for a healthy life that combines ICT technology with a competitive healthcare industry environment is becoming the next growth engine. Therefore, in this paper, artificial intelligence-based data analysis of the examination results was applied in the health examination process. Through this, a research was conducted to build a knowledge base modeling that can improve the reliability of the overall judgment. To this end, an algorithm was designed through deep learning analysis to calculate and verify the test result index. Then, the modeling that provides comprehensive examination information through judgment knowledge was studied. Through the application of the proposed modeling, it is possible to analyze and utilize big data on national health, so it can be expected to reduce medical expenses and increase health.