• Title/Summary/Keyword: 임상 데이터

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Perceptions Types of Workplace Bullying among Clinical Nurses (임상간호사의 태움에 대한 인식 유형)

  • Lee, Hye-Jin;Lee, Joo-Young;Lee, Do-Young
    • Journal of the Korea Convergence Society
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    • v.12 no.6
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    • pp.289-302
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    • 2021
  • This study is an exploratory study aimed at identifying the type and identifying type-specific characteristics by applying Q methodology to identify the perception of workplace bullying among clinical nurses. Methods: A total of 38 Q samples were selected and data were collected from 36 clinical nurses. Collected data were analyzed by the PC QUANL program. Six types have been identified about the clinical nurse's perception of workplace bullying. Type I-1 was "Endurance", I-2 was "Hazing", Type II-1 was "Rite of passage", Type II-2 was "Territorial individual", Type III-1 was "Hierarchical order", Type III-2 was "Interpersonal silent". These results can be useful in developing improvement programs such as interpersonal relationships and communication. In addition, practical strategies are required to improve the nursing work environment.

Diagnostic Methods of Respiratory Virus Infections and Infection Control (호흡기 바이러스 감염의 진단법과 감염관리)

  • Park, Chang-Eun
    • Korean Journal of Clinical Laboratory Science
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    • v.53 no.1
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    • pp.11-18
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    • 2021
  • Respiratory viruses (RVs) cause infections in hospital environments through direct contact with infected visitors. In infection control, it causes major problems of acquired infections in hospitals by respiratory viruses. The surveillance data derived from clinical laboratories are often used to properly allocate medical resources to hospitals and communities for treatment, consumables, and diagnostic product purchases in the institutions and public health sectors that provide health care. An early diagnosis is essential in infection with respiratory viruses, and methods that can be used in diagnostic methods using respiratory samples include virus culture, molecular diagnosis, and analysis. A microchip provides a new strategy for developing a more diverse and powerful technology called point-of-care testing. The importance of the respiratory system should be applied strictly to the infection control guidelines to ensure the occupational health and safety of health care workers. Evidence of clinical efficacy, including this study, is challenging the long-standing paradigm for infection propagation. Additional assistance will be needed for frequent tests to detect respiratory viruses in inpatients who have begun to show new respiratory symptoms indicating infections requiring efforts to control the infection.

An App-based Evolving Medical Nomogram Service System (앱기반 진화 의료 노모그램 서비스 시스템)

  • Lee, Keon-Myung;Hwang, Kyoung-Soon;Kim, Wun-Jae
    • Journal of Korea Entertainment Industry Association
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    • v.4 no.4
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    • pp.72-76
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    • 2010
  • Clinical nomogram is a graphical representation of numeric formula, constructed from clinical cases database of followed patients' treatment, which is used for medical predication. For a clinical nomogram to contribute patient care, it is required to accumulate as many as clinical cases and to extract medical prediction knowledge. It needs to be equipped with an effective method to build medical nomogram with high predication accuracy. It is desirable for medical nomogram to be accessible at patient care point. This paper proposes a medical nomogram service system architecture which takes into account the above-mentioned issues. The proposed system architecture includes a web-based database subsystem to maintain and keep track of clinical cases. On the periodic basis, a new clinical nomogram is reconstructed for the updated clinical database. For the convenient use of patient care practice environment, an app-based program is provided which makes prediction based on the most recent clinical nomogram constructed in the service system. The proposed method has been applied to a clinical nomogram service system development for recurrence and survival prediction in bladder cancer patients.

Study on Domestic Awareness of Korean Medicine Treatment for Dysmenorrhea using Big Data (빅데이터를 활용한 월경통에 대한 국내 한방 치료 인식 조사)

  • Ha-Young Jeon;Deok-Sang Hwang;Jin-Moo Lee;Chang-Hoon Lee;Jun-Bock Jang
    • The Journal of Korean Obstetrics and Gynecology
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    • v.37 no.3
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    • pp.20-32
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    • 2024
  • Objectives: The purpose of this study is to investigate the domestic awareness of Korean medicine treatment for dysmenorrhea. Methods: We conducted word frequency analysis, 2-gram analysis, degree centrality analysis, and CONCOR analysis using big data searched for '월경통', '생리통', and '한방' as main key words. The searching period was set from 2019 to 2023. Results: The number of original text data searched through main key words was on the rise. Specific words related to Korean medicine treatment were in the top 100, words related to herbal medicine ranked particularly high. The top 100 words were divided into 4 clusters (A; Body parts or body substances related to dysmenorrhea, B; Symptoms that accompany dysmenorrhea, C; Physiological or pathological situations related to dysmenorrhea, and D; Treatment related words of dysmenorrhea) and some clusters showed close relationships between each others (B-C, B-D, and C-D). Conclusions: Our results suggest that interest in Korean medicine treatment for dysmenorrhea is increasing. Also, as public understanding is estimated to be high, specific information such as method, process and mechanism of Korean medicine treatment seems to be needed.

Fuzzy discretization with spatial distribution of data and Its application to feature selection (데이터의 공간적 분포를 고려한 퍼지 이산화와 특징선택에의 응용)

  • Son, Chang-Sik;Shin, A-Mi;Lee, In-Hee;Park, Hee-Joon;Park, Hyoung-Seob;Kim, Yoon-Nyun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.2
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    • pp.165-172
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    • 2010
  • In clinical data minig, choosing the optimal subset of features is such important, not only to reduce the computational complexity but also to improve the usefulness of the model constructed from the given data. Moreover the threshold values (i.e., cut-off points) of selected features are used in a clinical decision criteria of experts for differential diagnosis of diseases. In this paper, we propose a fuzzy discretization approach, which is evaluated by measuring the degree of separation of redundant attribute values in overlapping region, based on spatial distribution of data with continuous attributes. The weighted average of the redundant attribute values is then used to determine the threshold value for each feature and rough set theory is utilized to select a subset of relevant features from the overall features. To verify the validity of the proposed method, we compared experimental results, which applied to classification problem using 668 patients with a chief complaint of dyspnea, based on three discretization methods (i.e., equal-width, equal-frequency, and entropy-based) and proposed discretization method. From the experimental results, we confirm that the discretization methods with fuzzy partition give better results in two evaluation measures, average classification accuracy and G-mean, than those with hard partition.

A Study on the Mapping Method of IEEE 11073 DIM/HL7 v3 RIM for Smart health-care (스마트폰 헬스케어를 위한 IEEE 11073 DIM/HL7 v3 RIM 매핑 방법에 대한 연구)

  • Kim, Jong-Pan;Jeon, Jae-Hwan;Oh, Am-Suk
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.842-845
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    • 2012
  • 의료기기는 헬스케어 서비스를 위한 필수요소로 최근 의료와 관련된 스마트폰 애플리케이션의 증가와 함께 스마트폰과 연결되는 의료기기를 활용한 스마트 헬스케어가 대두되고 있다. 이러한 스마트 헬스케어는 현재 ISO/IEEE 11073 표준을 통해 의료기기와 게이트웨이를 연결하여 임상정보를 전송하고 게이트웨이는 HL7 CDA 표준 문서를 통해 전자 건강 기록 및 개인 건강 기록 시스템, 임상 워크플로우 및 임상 의사 결정 지원 시스템과 같은 유형의 의료 서비스 시스템과 연동하는 솔루션이다. ISO/IEEE 11073은 DIM(Domain Information Model)이라는 정보 모델을 기반으로 하며 HL7 v3인 CDA는 RIM(Reference Information Model)이 있기 때문에 상이한 인터페이스간의 매핑 매커니즘을 필요로 한다. 이에 본 논문에서는 스마트폰 환경에서 의료 응용 애플리케이션에서의 효율적인 의료기기 데이터 운용을 위해 RMIM(Refined Message Information Model) 기반의 IEEE 11073 DIM/HL7 v3 RIM 표준 인터페이스 변환 방법을 제안한다.

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Comparison of Estimation Methods in NONMEM 7.2: Application to a Real Clinical Trial Dataset (실제 임상 데이터를 이용한 NONMEM 7.2에 도입된 추정법 비교 연구)

  • Yun, Hwi-Yeol;Chae, Jung-Woo;Kwon, Kwang-Il
    • Korean Journal of Clinical Pharmacy
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    • v.23 no.2
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    • pp.137-141
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    • 2013
  • Purpose: This study compared the performance of new NONMEM estimation methods using a population analysis dataset collected from a clinical study that consisted of 40 individuals and 567 observations after a single oral dose of glimepiride. Method: The NONMEM 7.2 estimation methods tested were first-order conditional estimation with interaction (FOCEI), importance sampling (IMP), importance sampling assisted by mode a posteriori (IMPMAP), iterative two stage (ITS), stochastic approximation expectation-maximization (SAEM), and Markov chain Monte Carlo Bayesian (BAYES) using a two-compartment open model. Results: The parameters estimated by IMP, IMPMAP, ITS, SAEM, and BAYES were similar to those estimated using FOCEI, and the objective function value (OFV) for diagnosing the model criteria was significantly decreased in FOCEI, IMPMAP, SAEM, and BAYES in comparison with IMP. Parameter precision in terms of the estimated standard error was estimated precisely with FOCEI, IMP, IMPMAP, and BAYES. The run time for the model analysis was shortest with BAYES. Conclusion: In conclusion, the new estimation methods in NONMEM 7.2 performed similarly in terms of parameter estimation, but the results in terms of parameter precision and model run times using BAYES were most suitable for analyzing this dataset.

Design and Implementation of Emergency Medical System based on the Standard of HL7 Message for Utilization of Patient Medical Information (환자 임상정보 활용을 위한 HL7기반 응급의료시스템의 설계 및 구현)

  • Kim, Jong-Pan;Oh, Am-Suk
    • Journal of Korea Multimedia Society
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    • v.14 no.2
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    • pp.295-306
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    • 2011
  • The existing emergency medical systems are unable to obtain accurate clinical information, so most of the specialized first aid is being done within the hospital. In this paper, designed medical information transfer structure based on medical information standards HL7 for accurate first aid is proposed. The designed system can share clinical information and emergency medical information in terms of standard HL7 messages. Therefore, the correct first aid is available in steps taken by the hospital. In addition, the system of this paper has been implemented based on the OSGi service platform for the efficient integration with other health-related services.

Adjusted maximum tolerated dose estimation by stopping rule in phaseⅠclinical trial (제 1상 임상시험에서 멈춤 규칙을 이용한 수정된 최대허용용량 추정법)

  • Park, Ju Hee;Kim, Dongjae
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1085-1091
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    • 2012
  • Phase I clinical trials are designed to identify an appropriate dose; the maximum tolerated dose, which assures safety of a new drug by evaluating the toxicity at each dose-level. The adjusted maximum tolerated dose estimation is presented by stopping rule in phase I clinical trial on this research. The suggested maximum tolerated dose estimation is compared to the standard method3 and NM method using a Monte Carlo simulation study.

Independent Data Monitoring Committees: Review of Current Guidelines (국내 및 해외의 임상시험 데이터모니터링위원회 지침의 현황)

  • Lee, Bo Ram;Lee, Kyung Eun
    • Korean Journal of Clinical Pharmacy
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    • v.26 no.2
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    • pp.181-186
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    • 2016
  • Background: There has been on increasing emphasis on the importance of monitoring the safety of participants in a clinical trial to protect patients and maintain the integrity of the trial. The independent data monitoring committee (IDMC) has become common component of randomized clinical trials in recent years. Methods: It is important to consider the implications of different approaches that are being used in various countries. IDMC guidelines in Korea, US, and Europe were reviewed and compared to provide the objective, composition and operation of IDMC in detail. Results: IDMC is a group of experts in related subject are as who perform interim data monitoring to make a recommendation to the sponsor or organizer regarding appropriateness of trial continuation and the need for modifications of the trial. Independence of IDMC is preferred in order to minimize influence of factors unrelated to scientific, medical and ethical considerations that should underlie decision-making. Conclusion: IDMC has become an increasingly important component of clinical trials in recent years. Practical operating procedures need to be developed considering the future regulatory status of data monitoring committees.