• Title/Summary/Keyword: Disease Database

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Cohort Profile: Korean Tuberculosis and Post-Tuberculosis Cohort Constructed by Linking the Korean National Tuberculosis Surveillance System and National Health Information Database

  • Jeong, Dawoon;Kang, Hee-Yeon;Kim, Jinsun;Lee, Hyewon;Yoo, Bit-Na;Kim, Hee-Sun;Choi, Hongjo
    • Journal of Preventive Medicine and Public Health
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    • v.55 no.3
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    • pp.253-262
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    • 2022
  • We aimed to review the current data composition of the Korean Tuberculosis and Post-Tuberculosis Cohort, which was constructed by linking the Korean Tuberculosis Surveillance System (KNTSS; established and operated by the Korean Disease Control and Prevention Agency since 2000) and the National Health Information Database (NHID; established by the National Health Insurance Service in 2012). The following data were linked: KNTSS data pertaining to patients diagnosed with tuberculosis between 2011 and 2018, NHID data of patients with a history of tuberculosis and related diseases between 2006 and 2018, and data (obtained from the Statistics Korea database) on causes of death. Data from 300 117 tuberculosis patients (177 206 men and 122 911 women) were linked. The rate of treatment success for new cases was highest in 2015 (86.7%), with a gradual decrease thereafter. The treatment success rate for previously treated cases showed an increasing trend until 2014 (79.0%) and decreased thereafter. In total, 53 906 deaths were confirmed among tuberculosis patients included in the cohort. The Korean Tuberculosis and Post-Tuberculosis Cohort can be used to analyze different measurement variables in an integrated manner depending on the data source. Therefore, these cohort data can be used in future epidemiological studies and research on policy-effect analysis, treatment outcome analysis, and health-related behaviors such as treatment discontinuation.

Medical issues to consider for establishing the concept of Mibyeong (미병(未病)의 의학적 개념 정립을 위해 고려해야 할 주제들)

  • Nam, Donghyun;Han, Kyungsook
    • The Journal of the Society of Korean Medicine Diagnostics
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    • v.24 no.1
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    • pp.1-13
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    • 2020
  • Objectives Mibyeong is an ideological concept that means the state between the healthy and diseased conditions. The purpose of this study was to suggest a research direction to establish the diagnostic criteria for the Mibyeong by reviewing the research results for the Mibyeong. Methods Academic databases (OASIS for Korean database, Embase for English database, and CNKI for Chinese database) were used to search related literatures, and articles describing the concept or diagnostic criteria of the disease were selected. Results The concept of Mibyeong consisted of three different conditions: (1) subjective symptoms without a specific disease, (2) abnormal examination findings without a specific disease, and (3) a state in between health and disease. No matter which of the three conditions is applied, the spectrum of condition was very wide and diverse. Conclusions It is impossible to apply appropriate and monolithic diagnostic criteria to all types of Mibyeong. Therefore, we suggests that the Mibyeong be classified into several subtypes and the diagnostic criteria suitable for each type be established.

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Herbal Medicine for the Treatment of Non-Erosive Reflux Disease: A Systematic Review and Meta-Analysis Protocol

  • Minjeong Kim;Chaehyun Park;Jae-Woo Park;Jinsung Kim;Seok-Jae Ko
    • The Journal of Internal Korean Medicine
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    • v.44 no.6
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    • pp.1176-1185
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    • 2023
  • Introduction: Non-erosive reflux disease (NERD) is the most common subtype of gastroesophageal reflux disease (GERD). This study aims to synthesize evidence on the efficacy and safety of various herbal medicines for the treatment of NERD. Methods and analysis: Ten electronic databases will be examined: MEDLINE (via PubMed), Cochrane Central Register of Controlled Trials, Embase, Allied and Complementary Medicine Database, China National Knowledge Infrastructure Database, Citation Information by Nii, Korean Medical Database, Korean Studies Information Service System, National Digital Science Library, and Oriental Medicine Advanced Searching Integrated System. All randomized controlled trials published from inception to May 2023 that meet the eligibility criteria will be selected. Two independent researchers will extract data, such as publication year, study design, intervention details, outcome measures, main results, and adverse events. The risk of bias and quality of evidence will be assessed, and subgroup analyses will be performed according to the type of control intervention and herbal medicine. The analysis process will be conducted using Review Manager 5.4 software. Discussion: This review will present a summary and rationale for herbal medicine's effectiveness in treating NERD. The findings of this review can help those who want to apply herbal medicine to the treatment of NERD.

Native Pig and Chicken Breed Database: NPCDB

  • Jeong, Hyeon-Soo;Kim, Dae-Won;Chun, Se-Yoon;Sung, Samsun;Kim, Hyeon-Jeong;Cho, Seoae;Kim, Heebal;Oh, Sung-Jong
    • Asian-Australasian Journal of Animal Sciences
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    • v.27 no.10
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    • pp.1394-1398
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    • 2014
  • Indigenous (native) breeds of livestock have higher disease resistance and adaptation to the environment due to high genetic diversity. Even though their extinction rate is accelerated due to the increase of commercial breeds, natural disaster, and civil war, there is a lack of well-established databases for the native breeds. Thus, we constructed the native pig and chicken breed database (NPCDB) which integrates available information on the breeds from around the world. It is a nonprofit public database aimed to provide information on the genetic resources of indigenous pig and chicken breeds for their conservation. The NPCDB (http://npcdb.snu.ac.kr/) provides the phenotypic information and population size of each breed as well as its specific habitat. In addition, it provides information on the distribution of genetic resources across the country. The database will contribute to understanding of the breed's characteristics such as disease resistance and adaptation to environmental changes as well as the conservation of indigenous genetic resources.

Application of Pharmacovigilance Methods in Occupational Health Surveillance: Comparison of Seven Disproportionality Metrics

  • Bonneterre, Vincent;Bicout, Dominique Joseph;De Gaudemaris, Regis
    • Safety and Health at Work
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    • v.3 no.2
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    • pp.92-100
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    • 2012
  • Objectives: The French National Occupational Diseases Surveillance and Prevention Network (RNV3P) is a French network of occupational disease specialists, which collects, in standardised coded reports, all cases where a physician of any specialty, referred a patient to a university occupational disease centre, to establish the relation between the disease observed and occupational exposures, independently of statutory considerations related to compensation. The objective is to compare the relevance of disproportionality measures, widely used in pharmacovigilance, for the detection of potentially new disease ${\times}$ exposure associations in RNV3P database (by analogy with the detection of potentially new health event ${\times}$ drug associations in the spontaneous reporting databases from pharmacovigilance). Methods: 2001-2009 data from RNV3P are used (81,132 observations leading to 11,627 disease ${\times}$ exposure associations). The structure of RNV3P database is compared with the ones of pharmacovigilance databases. Seven disproportionality metrics are tested and their results, notably in terms of ranking the disease ${\times}$ exposure associations, are compared. Results: RNV3P and pharmacovigilance databases showed similar structure. Frequentist methods (proportional reporting ratio [PRR], reporting odds ratio [ROR]) and a Bayesian one (known as BCPNN for "Bayesian Confidence Propagation Neural Network") show a rather similar behaviour on our data, conversely to other methods (as Poisson). Finally the PRR method was chosen, because more complex methods did not show a greater value with the RNV3P data. Accordingly, a procedure for detecting signals with PRR method, automatic triage for exclusion of associations already known, and then investigating these signals is suggested. Conclusion: This procedure may be seen as a first step of hypothesis generation before launching epidemiological and/or experimental studies.

Analysis of the Active Compounds and Therapeutic Mechanisms of Yijin-tang on Meniere's Disease Using Network Pharmacology(I) (네트워크 약리학을 활용한 메니에르병에 대한 이진탕(二陳湯)의 활성 성분과 치료 기전 연구(I))

  • SunKyung Jin;Hae-Jeong Nam
    • The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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    • v.36 no.1
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    • pp.50-63
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    • 2023
  • Objectives : This study used a network pharmacology approach to explore the active compounds and therapeutic mechanisms of Yijin-tang on Meniere's disease. Methods : The active compounds of Yijin-tang were screened via the TCMSP database and their target proteins were screened via the STITCH database. The GeneCard was used to establish the Meniere's disease-related genes. The intersection targets were obtained through Venny 2.1.0. The related protein interaction network was constructed with the STRING database, and topology analysis was performed through CytoNCA. GO biological function analysis and KEGG enrichment analysis for core targets were performed through the ClueGO. Results : Network analysis identified 126 compounds in five herbal medicines of Yijin-tang. Among them, 15 compounds(naringenin, beta-sitosterol, stigmasterol, baicalein, baicalin, calycosin, dihydrocapsaicin, formononetin, glabridin, isorhamnetin, kaempferol, mairin, quercetin, sitosterol, nobiletin) were the key chemicals. The target proteins were 119, and 7 proteins(TNF, CASP9, PARP1, CCL2, CFTR, NOS2, NOS1) were linked to Meniere's disease-related genes. Core genes in this network were TNF, CASP9, and NOS2. GO/KEGG pathway analysis results indicate that these targets are primarily involved in regulating biological processes, such as excitotoxicity, oxidative stress, and apoptosis. Conclusion : Pharmacological network analysis can help to explain the applicability of Yijin-tang on Meniere's disease.

Validation of Administrative Big Database for Colorectal Cancer Searched by International Classification of Disease 10th Codes in Korean: A Retrospective Big-cohort Study

  • Hwang, Young-Jae;Kim, Nayoung;Yun, Chang Yong;Yoon, Hyuk;Shin, Cheol Min;Park, Young Soo;Son, Il Tae;Oh, Heung-Kwon;Kim, Duck-Woo;Kang, Sung-Bum;Lee, Hye Seung;Park, Seon Mee;Lee, Dong Ho
    • Journal of Cancer Prevention
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    • v.23 no.4
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    • pp.183-190
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    • 2018
  • Background: As the number of big-cohort studies increases, validation becomes increasingly more important. We aimed to validate administrative database categorized as colorectal cancer (CRC) by the International Classification of Disease (ICD) 10th code. Methods: Big-cohort was collected from Clinical Data Warehouse using ICD 10th codes from May 1, 2003 to November 30, 2016 at Seoul National University Bundang Hospital. The patients in the study group had been diagnosed with cancer and were recorded in the ICD 10th code of CRC by the National Health Insurance Service. Subjects with codes of inflammatory bowel disease or tuberculosis colitis were selected for the control group. For the accuracy of registered CRC codes (C18-21), the chart, imaging results, and pathologic findings were examined by two reviewers. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for CRC were calculated. Results: A total of 6,780 subjects with CRC and 1,899 control subjects were enrolled. Of these patients, 22 subjects did not have evidence of CRC by colonoscopy, computed tomography, magnetic resonance imaging, or positron emission tomography. The sensitivity and specificity of hospitalization data for identifying CRC were 100.00% and 98.86%, respectively. PPV and NPV were 99.68% and 100.00%, respectively. Conclusions: The big-cohort database using the ICD 10th code for CRC appears to be accurate.

Data Mining Approach for Diagnosing Heart Disease (심장 질환 진단을 위한 데이터 마이닝 기법)

  • Noh, Ki-Yong;Ryu, Keun-Ho;Lee, Heon-Gyu
    • Science of Emotion and Sensibility
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    • v.10 no.2
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    • pp.147-154
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    • 2007
  • Electrocardiogram(ECG) being the recording of the heart's electrical activity provides valuable clinical information about heart's status. Many researches have been pursued for heart disease diagnosis using ECG so far. However, electrocardio-graph uses foreign diagnosis algorithm in the con due to inaccuracy of domestic diagnosis results for a heart disease. This paper proposes ST-segment extraction technique diagnosing heart disease parameter from raw ECG data. As the ST-segment is used for prediction of Coronary Artery Disease, we can predict heart disease using classification approach in data mining technique. We can also predict patient's clinical characterization from patient clinical data.

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Comparison of network pharmacology based analysis on White Ginseng and Red Ginseng (인삼(人蔘)과 홍삼(紅蔘)의 네트워크 약리학적 분석 결과 비교)

  • Park, Sohyun;Lee, Byoungho;Jin, Myungho;Cho, Suin
    • Herbal Formula Science
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    • v.28 no.3
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    • pp.243-254
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    • 2020
  • Objectives : Network pharmacology analysis is commonly used to investigate the synergies and potential mechanisms of multiple compounds by analyzing complex, multi-layered networks. We used TCMSP and BATMAN-TCM databases to compare results of network pharmacological analysis between White Ginseng(WG) and Red Ginseng(RG). Methods : WG and RG were compared with components and their target molecules using TCMSP database, and compound-target-pathway/disease networks were compared using BATMAN-TCM database. Results : Through TCMSP, 104 kinds of target molecules were derived from WG and 38 kinds were derived from RG. Using the BATMAN-TCM database, target pathways and diseases were screened, and more target pathways and diseases were screened compared to RG due to the high composition of WG ingredients. Analysis of component-target-pathway/disease network using network analysis tools provided by BATMAN-TCM showed that WG formed more networks than RG. Conclusions : Network pharmacology analysis can be effectively performed using various databases used in system biology research, and although the materials that have been reported in the past can be used efficiently for research on diseases related to targets, the results are unreliable if prior studies are focused on limited or narrow research areas.

CAD for Detection of Brain Tumor Using the Symmetry Contribution From MR Image Applying Unsharp Mask Filter

  • Kim, Dong-Hyun;Ye, Soo-Young
    • Transactions on Electrical and Electronic Materials
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    • v.15 no.4
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    • pp.230-234
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    • 2014
  • Automatic detection of disease helps medical institutions that are introducing digital images to read images rapidly and accurately, and is thus applicable to lesion diagnosis and treatment. The aim of this study was to apply a symmetry contribution algorithm to unsharp mask filter-applied MR images and propose an analysis technique to automatically recognize brain tumor and edema. We extracted the skull region and drawed outline of the skull in database of images obtained at P University Hospital and detected an axis of symmetry with cerebral characteristics. A symmetry contribution algorithm was then applied to the images around the axis of symmetry to observe intensity changes in pixels and detect disease areas. When we did not use the unsharp mask filter, a brain tumor was detected in 60 of a total of 95 MR images. The disease detection rate for the brain was 63.16%. However, when we used the unsharp mask filter, the tumor was detected in 87 of a total of 95 MR images, with a disease detection rate of 91.58%. When the unsharp mask filter was used in the pre-process stage, the disease detection rate for the brain was higher than when it was not used. We confirmed that unsharp mask filter can be used to rapidly and accurately to read many MR images stored in a database.