• Journal of Korea Artificial Intelligence Association
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• v.1 no.1
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• pp.17-21
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• 2023

The primary objective of this research is to utilize machine learning models to analyze factors tailored to each dataset for predicting mental health conditions. The study aims to develop appropriate models based on specific datasets, with the goal of accurately predicting mental health states through the analysis of distinct factors present in each dataset. This approach seeks to design more effective strategies for the prevention and intervention of depression, enhancing the quality of mental health services by providing personalized services tailored to individual circumstances. Overall, the research endeavors to advance the development of personalized mental health prediction models through data-driven factor analysis, contributing to the improvement of mental health services on an individualized basis.

• IE interfaces
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• v.21 no.2
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• pp.209-220
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• 2008

Recently, innovative medical services are fast emerging, which include customized medical services based on bio-informatics, composition of cure and well-being exploiting ubiquitous technology, hospital supply chain management using RFID, and so forth. However, conventional approaches for new service development hardly give us systematic model to analyze and produce creative medical services. Because most of them are static and concentrate on microscopic tools or techniques. Thus, it is highly desirable to suggest an integrative framework to organize the whole transformation process from technology to medical service. The objective of this study is to propose a medical service engineering model based on the dynamic innovation theory. The proposed model contains objectives of service system, strategies of hospital, stages, activities required to deal with medical service life cycle, which incorporates the acquisition of new technology, transformation to the product, penetration into market, and adoption of consumers. In addition, the usefulness and applicability of the newly proposed model are provided using catholic medical center example.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.177-190
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• 2011

Due to the growth of economy and the advancement of IT, the life expectancy has been prolonged and the interests in health have greatly increased. Recently the request for systems that enable measuring the bio-signals of patients in the non medical organizations, such as home, and transmitting them to medical staffs at remote sites for monitoring them. In this paper, we present an agent-based u-health system for patients or suspects with heart diseases. Our system consists of portable devices for measuring bio-signals and agents that perform data collection, data storage, automatic detection of abnormal status in patients, and HL7-based data exchange in a cooperative way. The main features of the system are : the agent-based architecture facilitates the addition of new service modules as well as the modification of existing ones; an intelligent agent is provided which automatically detects situations in which the bio-signals of patients are abnormal; the medical data standard is supported so that the communication with other systems is very easy. To our survey, there have been few previous systems which support all those features in a seamless way.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.8
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• pp.245-250
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• 2014

In recent years, the developments of medical technology and emergency medical services have been changed to home from the hospital. In this regard, the researches for the prevention or early diagnosis have become actively. In particular, bio-signal monitoring is applied to a variety of u-healthcare application services. The proposed system in this paper is to provide a security technology to protect the medical information measured from the various sensors. Especially, bio-signal information is privacy-sensitive personal information that must be protected. We applied a two-dimensional code technology, QR code, for the protection and management. In the client side, it can analyze the QR code and confirm the results on devices. Finally, with this proposed platform, we show the results of application service to verify the creation and distribution of integrated image file between the bio-signal and medical image information.

• 한국약용작물학회:학술대회논문집
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• 2011.09a
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• pp.352-353
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• 2011

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.89-101
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• 2012

This paper presents development of a management system for the health and diseases of the elderly. This study aimed to the promotion of the u-healthcare industry and to the increase in its competitive power by developing and expanding a system for managing the health and diseases of the elderly, in cooperation with u-healthcare companies. The study is underway through the following four substudies. In the first substudy titled development of the bio-signal collection and analysis technology using smart media, a technology that supports the collection of bio-signals in the elderly using portable terminals. In the second substudy titled development of the patient-specific healthcare platform expansion and enhancement technology, a technology is being developed for making medical decisions and taking measures based on the results of the processing of the collected bio-signals. In the third substudy titled development of the N-screen based healthcare contents open service technology, a technology is being developed to provide information on health, diseases, and medicine to platforms. In the fourth substudy titled development of the oriental medicine diagnosis and analysis technology for senile diseases. This study is expected to help ensure an excellent workforce and new technologies in the healthcare sector using smart phones, and to help reduce medical expenses by improving the health of citizens.

• KIEAE Journal
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• v.14 no.6
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• pp.23-29
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• 2014

It is essential to investigate the structure and the main characteristics of BSN (Bio-Sensor Network) platform in built smart healthcare environment while designing healthy housing facilities. For this study, WSN (Wireless Sensor Network) data transmission technologies have been employed with medical sensors, and optimal medical devices would provide various Web 2.0 services by connecting to the WiBro network. The BSN platform normally recognizes in surroundings of WBAN (Wireless Body Area Network) or WPAN (Wireless Personal Area Network), and it is possible to manage sensor nodes by utilizing SOAP (Simple Object Access Protocol) and REST (REpresentational State Transfer). In addition, the feature of SNMP (Simple Network Management Protocol) for mobile gateway is also included for being adapted to huge network structure. Finally, BSN platform will play a role as important clues for developing personal WSN service models for smart healthy housing properties.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.1
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• pp.62-69
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• 2008

In this paper, we proposed the real-time bio-signals monitoring system that is based on the ZigBee wireless sensor network and SIP. This system makes medical team and user easily confirm user's medical state irrelative to their location and time. The communication between medical sensors and the user's end device uses the ZigBee wireless sensor network. The power consumption was decreased because wireless sensor network does not use the Ad-hoc routing protocol but routing protocol that is based on tree structure. Our proposed system includes a wireless user's end device, monitoring console, SIP server and database server. This real-time bio-signals monitoring system makes possible to implement the U-health care services and improving efficiency of medical treatment services.

• Food Science and Industry
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• v.54 no.3
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• pp.145-159
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• 2021

Conventional nutrition services involve producer-oriented approaches without considering the differences in the characteristics and circumstances of each individual, whereas personalized nutrition services are consumer-oriented concepts that provide products and services for maintaining optimal health conditions based on the genetic, physiological, and metabolic characteristics of individuals, with these products based on balanced nutrition and healthy living. Currently, methods for evaluating dietary habits, monitoring dietary behaviors, deep phenotyping, and metabotyping via microbiota profiling, as well as methods for predicting big data by using machine learning, have been previously studied in Korea and abroad. With the development of medical technology and the improvement of hygiene, the demand for personalized nutrition and health services for healthier, happier, and more satisfying lives is rapidly increasing. Therefore, based on scientific technologies, attempts are needed to advance these services into global personalized markets and to boost the global competitiveness of countries and companies.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.109-115
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• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.