• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.513-516
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• 2013

In this paper, we present an information collecting system in medical information management domain. Our proposed system performs a systemized process, consisting of collection, transmission, and management, to develop intelligent medical information system and medical big data processing system. Our information collecting system consists of low-power biomedical sensors, biomedical information collecting devices, and storage systems. Currently, almost biomedical information of patients is collected manually by employees like nurses and medical doctors. Therefore, collected biometric data can be error-pronoun data. Since there is a lack to make big data of medical information, it is difficult to enhance the quality of medical services and researches. Accordingly, through our proposed system, we can overcome the problems like error-pronoun biometric data. In addition, we can extremely extend the area of collectable biometric data. Furthermore, using this system, we are able to make a real-time biomedical analysis system, like a real-time patient diagnosis system, and establish a strategy to against future medical markets changing rapidly.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1945-1950
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• 2003

Conceived to acquire personal information for an electronic medical record, the clinical interview contains probing questions. The number and type of inquiries are assumed to fulfill medical protocols, and therefore are deemed essential for treatment - but the rate can and should be controlled. High rates of inquiry merely intimidate the patient and affect replies. The purpose of this paper is to mathematically formulate permissible rates of clinical interviews held during telehomecare virtual visits and designed to avoid patient anxiety. Mental stress is derived as a function of the weight of importance assigned by the patient, virtual visit duration, and the rate of questioning in the direction of greater sensitivity. Two operations are of interest: Collecting and recording information by the provider, and maintaining synchrony of questions and answers by the patient. The Lorentz transformation yields the patient’s view of the operational rates. Conservation of information momentum is postulated and applied before and after replies are recorded. It is shown that the weight of importance designated by the patient to collecting and recording personal information is driven by a singularity that depends on the rate of questioning. The findings should serve as a guideline in interviewer training programs.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.817-837
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• 2019

The medical industry is rapidly evolving into a combination of artificial intelligence (AI) and ICT technology, such as mobile health, wireless medical, telemedicine and precision medical care. Medical artificial intelligence can be diagnosed and treated, and autonomous surgical robots can be operated. For smart medical services, data such as medical information and personal medical information are needed. AI is being developed to integrate with companies such as Google, Facebook, IBM and others in the health care field. Telemedicine services are also becoming available. However, security issues of medical information for smart medical industry are becoming important. It can have a devastating impact on life through hacking of medical devices through vulnerable areas. Research on medical information is proceeding on the necessity of privacy and privacy protection. However, there is a lack of research on the practical measures for protecting medical information and the seriousness of security threats. Therefore, in this study, we want to confirm the research trend by collecting data related to medical information in recent 5 years. In this study, smart medical related papers from 2014 to 2018 were collected using smart medical topics, and the medical information papers were rearranged based on this. Research trend analysis uses topic modeling technique for topic information. The result constructs topic network based on relation of topics and grasps main trend through topic.

• The Korean Society of Law and Medicine
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• v.9 no.2
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• pp.339-382
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• 2008

Medical information is one of significant private information that includes in-dividual's own diverse information. Once opened, it exposes one's health condition and medical history to a third party, which could bring about serious troubles. On this account, the third parties are of much concerns about the information. If medical information collected through various routes is used with another purpose, oilier than the initial intention, it might cause serious results beyond one's control. Thus, it is essential to keep the information confidential. Also, the discrimination based on the medical information ought to be banned because it is likely to happen that exposed information socially stigmatizes a person, being discriminated in a work place or a school when he/she is employed or gets an insurance. In the current system, only medical institutions are responsible for protecting or securing medical records. Despite the information technology development and the increased interests in medical information, there are quite a few limitations in legal, technical, and administrative aspects. All kinds of organizations, involved in collecting and using the information, as well as medical institutions primarily producing and managing it should share the responsibilities.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1083-1090
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• 2022

Since renal cell carcinoma(RCC) has various examination and treatment methods according to clinical stage and histopathological characteristics, it is required to determine accurate and efficient treatment methods in the clinical field. However, the process of collecting and processing RCC medical data is difficult and complex, so there is currently no AI-based clinical decision support system for RCC treatments worldwide. In this study, we propose a clinical decision support system that helps clinicians decide on a precision treatment to each patient. RCC standard big database is built by collecting structured and unstructured data from the standard common data model and electronic medical information system. Based on this, various machine learning classification algorithms are applied to support a better clinical decision making.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.973-976
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• 2015

Inernet of Things(IoT) is interaction with each other, collecting, sharing, and analysing the data. IoT has been noted in combining the fields of medical service in particular. However, the security issue is caused, while IoT is receiving attention. U-Health and medical devices, which deal mainly the personal health information, is required to a high level of privacy and security of health information. This study analyzes cases of leakage of personal medical information, security of IoT, privacy flow, and the response strategies.

• Journal of Society of Preventive Korean Medicine
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• v.14 no.1
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• pp.59-76
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• 2010

Background : The system for collecting and managing the terminologies of Korean oriental medicine is essential to facilitate researches of developing intelligent information architecture based on ontology. Objectives : The purpose of this paper is to develop system for collecting and managing system for terminologies of Korean oriental medicine. Methods : First we defined roles of users used in this system, and define the system workflow based on them. Then we developed web-based collecting and managing system in which multiuser can work simultaneously, and it is compose of relational database system. Results : The terminologies of Korean Oriental Medicine can be efficiently collected, purified, inspected, and utilized by using proposed system. Conclusions : The system, proposed in this paper, can be used the whole field of oriental medicines for basic technology and has great contributions to make intelligent information architecture of oriental medicine based on ontology concept.

• KIISE Transactions on Computing Practices
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• v.23 no.5
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• pp.284-292
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• 2017

With the development of Internet of Things (IoT) technology, the combination of ICT and medical services has been increasing to improve the quality of medical services. Using the IoTs, we can collect personal health information continuously in a patient's everyday life. We expect that this will improve the quality of medical service through analysis. However, the problem of ensuring the protection of personal information within the personal health information has been hampering the research, development, and application of such services. Other problems include lack of IoT devices and lack of user convenience for collecting health information about a patient's everyday life. Therefore, in this study, we construct a daily health information management service that can collect the health related information at any time and store this data in personal storage. This data is then only provided to the healthcare worker when necessary. We built a test bed for an IoT-based smart home platform and are currently conducting user experiments. Based on the results of this study, we are attempting to provide a high quality medical trial service based on daily health information through linkage with medical device manufacturers, medical clinics, insurance companies, etc. We expect the proposed health information management service will contribute to the revitalization of smart health care services via activating various health related IoT devices and analyzing daily health information.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.93-100
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• 2024

With the advent of the Fourth Industrial Revolution, cutting-edge technologies such as artificial intelligence, big data, the Internet of Things, and cloud computing are driving innovation across industries. These technologies are generating massive amounts of data that many companies are leveraging. However, there is a notable reluctance among users to share sensitive information due to the privacy risks associated with collecting personal data. This is particularly evident in the healthcare sector, where the collection of sensitive information such as patients' medical conditions poses significant challenges, with privacy concerns hindering data collection and analysis. This research presents a novel technique for collecting and analyzing medical data that not only preserves privacy, but also effectively extracts statistical information. This method goes beyond basic data collection by incorporating a strategy to efficiently mine statistical data while maintaining privacy. Performance evaluations using real-world data have shown that the propose technique outperforms existing methods in extracting meaningful statistical insights.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.161-168
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• 2018

Recently, the bio-sensing information systems for collecting and analysing human body information of a patient in real time in the field of medical information and healthcare information service are continuously increasing. Specially, various wearable devices such as a wrist, a garment, and a skin attachment type for supporting health information of a mobile user are rapidly increasing. Until now, there is no patch-type biometric information service model. Therefore, this paper presents a biometric information system model and the application examples to support biometric information sensing and health information service of mobile user with digital patch system as a new biometric information system. As a result, through this research, research issues based on digital patch system are searched to suggest the direction of continuous research.