• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.301-319
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• 2007

Nowadays the information environment enables users to access the traditional library collection as well as various digital information resources. In this rapidly changing environment, the use of digital information resources such as web sites, data, and homepages has increased. In this research, highly-cited authors' research outcomes as well as the research outcomes of the people, who cited the highly-cited authors' works, were extracted then compared with information stored in the medical colleges' digital libraries and the academic information portals in the clinical medicine area by using the citation information provided by Essential Science Indicators from ISI Web of knowledge. Out of 10,000 authors,146 people's homepages, which present research outcomes, were analyzed. The research outcomes listed in the homepages included journal papers, monographs, conference proceedings, and lecture notes. About 15% of the journal papers, 32% of the monographs, 48% of the conference proceedings, and 100% of lecture notes were accessible only through the homepages. The research outcomes accessible from the homepages were almost analogous to the ones available through the medical college's digital libraries and the academic information portals. Therefore, the digital library collection will be improved and expanded quantitatively and qualitatively by collecting and using the information in the homepages of the prestigious researchers.

• Journal of Medicine and Life Science
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• v.20 no.4
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• pp.141-157
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• 2023

Stroke is a leading cause of disability and death. The condition requires prompt diagnosis and treatment. The quality of care provided to patients with stroke can vary depending on the availability of medical resources, which in turn, can affect prognosis. Recently, there has been growing interest in using machine learning (ML) to support stroke diagnosis and treatment decisions based on large medical data sets. Current ML applications in stroke care can be divided into two categories: analysis of neuroimaging data and clinical information-based predictive models. Using ML to analyze neuroimaging data can increase the efficiency and accuracy of diagnoses. Commercial software that uses ML algorithms is already being used in the medical field. Additionally, the accuracy of predictive ML models is improving with the integration of radiomics and clinical data. is expected to be important for improving the quality of care for patients with stroke.

• Healthcare Informatics Research
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• v.24 no.4
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• pp.263-275
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• 2018

Objectives: Automated audiometry provides an opportunity to do audiometry when there is no direct access to a clinical audiologist. This approach will help to use hearing services and resources efficiently. The purpose of this study was to review studies related to automated audiometry by focusing on the implementation of an audiometer, the use of transducers and evaluation methods. Methods: This review study was conducted in 2017. The papers related to the design and implementation of automated audiometry were searched in the following databases: Science Direct, Web of Science, PubMed, and Scopus. The time frame for the papers was between January 1, 2010 and August 31, 2017. Initially, 143 papers were found, and after screening, the number of papers was reduced to 16. Results: The findings showed that the implementation methods were categorized into the use of software (7 papers), hardware (3 papers) and smartphones/tablets (6 papers). The used transducers were a variety of earphones and bone vibrators. Different evaluation methods were used to evaluate the accuracy and the reliability of the diagnoses. However, in most studies, no significant difference was found between automated and traditional audiometry. Conclusions: It seems that automated audiometry produces the same results compared with traditional audiometry. However, the main advantages of this method; namely, saving costs and increased accessibility to hearing services, can lead to a faster diagnosis of hearing impairment, especially in poor areas.

• Korean Journal of Clinical Pharmacy
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• v.21 no.4
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• pp.311-318
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• 2011

Misinformation and inappropriate use of medication has become one of the most pressing concerns in drug safety. The purpose of this study was to survey public perception on drug safety as well as the channels most relied upon providing such information. The survey was performed for patients or their families visiting pharmacies in a local city in Korea. Analysis was performed from 367 respondents to the survey. The contents of this survey revealed that consumers were aware of the fact that medications should not be taken at any higher dosage or more often than directed by their prescriptions. The survey revealed a general awareness that symptoms might not be relieved immediately by their medications. However, the perception that there could be adverse drug reaction (ADR) at therapeutic dose was low except among the young or highly educated members. Respondents recognized that skin rashes were the most whereas drowsiness was the least common ADR symptom. There was a high awareness of drug-food or drug-drug interactions except in the case of certain nutraceuticals. Doctors and pharmacists were ranked as the most reliable resources to the consumer for providing drug related information. However, public relations or education programs were in need since there were still not negligible numbers of consumers depending on personal experience rather than health professionals.

• Korean Journal of Clinical Pharmacy
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• v.30 no.4
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• pp.243-249
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• 2020

Background: Despite the increased use of direct-acting oral anticoagulants, warfarin is still recommended as first-line therapy in patients with mechanical valves or moderate to severe mitral stenosis. Anticoagulation management services (AMSs) are warranted for patients receiving warfarin therapy due to the complexity of warfarin dosing and large interpatient variability. To overcome limited health care resources, we developed a messenger app-based chatbot that provides information to patients taking warfarin. Methods: We developed "WafarinTalk" as an add-on to the open-source messenger app KakaoTalk. We developed the prototype chatbot after building a database containing seven categories: 1) dosage and indications, 2) drug-drug interactions, 3) drug-food interactions, 4) drug-diet supplement interactions, 5) monitoring, 6) adverse events, and 7) precautions. We then surveyed 30 pharmacists and 10 patients on chatbot reliability and on participant satisfaction. Results: We found that 80% of the pharmacists agreed on the consistency of chatbot responses and 44% agreed on the appropriateness of chatbot. Furthermore, 47% of pharmacists said that they were willing to recommend the chatbot to patients. Of the seven categories, information on drug-food interaction was the most useful; 90% of patients said they were satisfied with the chatbot and 100% of patients said they were willing to use it when they were unable to see a pharmacist. We updated the prototype chatbot with feedback from the survey. Conclusion: This study showed that warfarin-related information could be provided to patients through a messenger application-based chatbot.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.3-3
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• 2003

With biomedical literature expanding so rapidly, there is an urgent need to discover and organize knowledge extracted from texts. Although factual databases contain crucial information the overwhelming amount of new knowledge remains in textual form (e.g. MEDLINE). In addition, new terms are constantly coined as the relationships linking new genes, drugs, proteins etc. As the size of biomedical literature is expanding, more systems are applying a variety of methods to automate the process of knowledge acquisition and management. In my talk, I focus on the project, GENIA, of our group at the University of Tokyo, the objective of which is to construct an information extraction system of protein - protein interaction from abstracts of MEDLINE. The talk includes (1) Techniques we use fDr named entity recognition (1-a) SOHMM (Self-organized HMM) (1-b) Maximum Entropy Model (1-c) Lexicon-based Recognizer (2) Treatment of term variants and acronym finders (3) Event extraction using a full parser (4) Linguistic resources for text mining (GENIA corpus) (4-a) Semantic Tags (4-b) Structural Annotations (4-c) Co-reference tags (4-d) GENIA ontology I will also talk about possible extension of our work that links the findings of molecular biology with clinical findings, and claim that textual based or conceptual based biology would be a viable alternative to system biology that tends to emphasize the role of simulation models in bioinformatics.

• Research in Community and Public Health Nursing
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• v.5 no.2
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• pp.130-146
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• 1994

Our medical care system is trying to diversify in order to meet the client's needs, and to adjust to a medical environment which is changing very rapidly. Because current nursing theory and practice focus on holistic care, health care management, education, and research, contrary to the traditional emphasis on only assisting a physician, more autonomy and specialization for the implementation of nursing are required. Considering these trends and actual needs, the category of clinical nurse specialist should be established as soon as possible. In order to develop strategies for implementing this new professional specialty, the authors conducted a field survey and literature review of the current system in Korea. As a result, various obstacles and constraints were discovered as follows : 1) There are few accredited educational programs for the training of CNS's. 2) Several hospitals already have staff designated as clinical nurse specialist (CNS) even though the term CNS is not yet standardized or adopted in nationwide. 3) The role of the CNS is not clearly understood by the medical societies, or even nursing societies. A nurse who works in specific nursing areas such as central supply, kidney dialysis, intensive care, coronary care, etc. for a long time, considers herself /himself a CNS. Based upon the above findings, the following alternatives are recommended. 1) The role of the CNS should be defined according to specified functions and authority : professional autonomy ; counselling and educating patients and their familes, nurses, and even other medical personnel ; research on improvement of nursing ; and management of the nursing environment including medical resources, information, and cases. 2) the qualification of CNS should be attained only by a nurse who has an RN license and clinical experience of more than 3 years in a specific nursing field: passes a qualifying examination; and contributes to the professional development of peers, colleagues, and others. A master's degree should only be optional, because of the insufficient of graduate programs which are well designed for the CNS. 3) The CNS should initially be a head nurse rather than line staff in order to deal with as wide an experience base as possible. 4) The nursing specialty could be divided into two areas such as a clinical field and a community field. The clinical field could then be categorized by the Styles' classification such as diseases and pathogenics, systems, ages, acuity, skills/techniques, and function/role ; the community field could be classified according to work site.

• Journal of Preventive Medicine and Public Health
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• v.36 no.1
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• pp.39-46
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• 2003

Objectives : To investigate the availability and demand for overall cancer-related information, and to establish a basic plan for the construction of a cancer database and information system based on the research results from Korea. Methods : Postal and telephone surveys were carried out, between August 2001 and November 2001, of 323 affiliated faculty professors from medical universities and colleges in Korea. The data were analyzed with descriptive statistical methods, with regard to the present status and demand for health and cancer-related information. Results : Most (over 80%) subjects studied utilized the health-related information provided on Internet website from foreign countries, such as Medline, but similar comprehensive information system lacked in Korea. The construction of a cancer-related database of domestic research results was revealed to be in a great demand. Information on registration and statistics (52.8%), study results (48.5%) and study resources (37.4%) were the major ingredients required in the database. In constructing a database of the cancer-related research results, a full-text service, continuous updating of data, and the development of standardized user-friendly searching tool were regarded as the necessary components. The formulation of an information sharing system, regarding cancer-related clinical trials, was investigated as being quite feasible. Conclusion : This study demonstrated the great importance of cancer information systems, and much demand for an available cancer-related database based on Korean research results.

• Parasites, Hosts and Diseases
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• v.41 no.1
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• pp.1-16
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• 2003

Neospora caninum is a coccidian parasite of animals. It is a major pathogen for cattle and dogs and it occasionally causes clinical infections in horses, goats, sheep, and deer. Domestic dogs are the only known definitive hosts for N. caninum. It is one of the most efficiently transmitted parasite of cattle and up to 90% of cattle in some herds are infected. Transplacental transmission is considered the major route of transmission of N. caninum in cattle. Neospora caninum is a major cause of abortion in cattle in many countries. To elicit protective immunity against abortion in cows that already harbor a latent infection is a major problem. This paper reviews information on biology, diagnosis, epidemiology and control of neosporosis in animals.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.135-149
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• 2011

In this paper, we propose the high-risk group detection model for patients with high blood pressure using case-based reasoning. The proposed model can be applied for public health maintenance organizations to effectively manage knowledge related to high blood pressure and efficiently allocate limited health care resources. Especially, the focus is on the development of the model that can handle constraints such as managing large volume of data, enabling the automatic learning to adapt to external environmental changes and operating the system on a real-time basis. Using real data collected from local public health centers, the optimal high-risk group detection model was derived incorporating optimal parameter sets. The results of the performance test for the model using test data show that the prediction accuracy of the proposed model is two times better than the natural risk of high blood pressure.