• Title/Summary/Keyword: Disease Database

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StrokeBase: A Database of Cerebrovascular Disease-related Candidate Genes

  • Kim, Young-Uk;Kim, Il-Hyun;Bang, Ok-Sun;Kim, Young-Joo
    • Genomics & Informatics
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    • v.6 no.3
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    • pp.153-156
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    • 2008
  • Complex diseases such as stroke and cancer have two or more genetic loci and are affected by environmental factors that contribute to the diseases. Due to the complex characteristics of these diseases, identifying candidate genes requires a system-level analysis of the following: gene ontology, pathway, and interactions. A database and user interface, termed StrokeBase, was developed; StrokeBase provides queries that search for pathways, candidate genes, candidate SNPs, and gene networks. The database was developed by using in silico data mining of HGNC, ENSEMBL, STRING, RefSeq, UCSC, GO, HPRD, KEGG, GAD, and OMIM. Forty candidate genes that are associated with cerebrovascular disease were selected by human experts and public databases. The networked cerebrovascular disease gene maps also were developed; these maps describe genegene interactions and biological pathways. We identified 1127 genes, related indirectly to cerebrovascular disease but directly to the etiology of cerebrovascular disease. We found that a protein-protein interaction (PPI) network that was associated with cerebrovascular disease follows the power-law degree distribution that is evident in other biological networks. Not only was in silico data mining utilized, but also 250K Affymetrix SNP chips were utilized in the 320 control/disease association study to generate associated markers that were pertinent to the cerebrovascular disease as a genome-wide search. The associated genes and the genes that were retrieved from the in silico data mining system were compared and analyzed. We developed a well-curated cerebrovascular disease-associated gene network and provided bioinformatic resources to cerebrovascular disease researchers. This cerebrovascular disease network can be used as a frame of systematic genomic research, applicable to other complex diseases. Therefore, the ongoing database efficiently supports medical and genetic research in order to overcome cerebrovascular disease.

Analysis of 『Jinguiyaolue』 Prescriptions using Database (데이터베이스를 이용한 『금궤요략』 처방(處方) 분석 연구)

  • Kim, SeongHo;Kim, SungWon;Kim, KiWook;Lee, ByungWook
    • Journal of Korean Medical classics
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    • v.32 no.3
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    • pp.131-146
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    • 2019
  • Objectives : The aim of this paper is to study the methodology for effectively analyzing the "Jinguiyaolue" prescriptions using database, and to explore possibilities of applying the data construction and query produced in the process to comparative research with other texts in the future. Methods : Using "Xinbianzhongjingquanshu(新編仲景全書)" as original script, the contents of "Jinguiyaolue" were entered into the database, in which one verse would be separated according to content for individual usage. Also, data with medicinal construction and disease pattern information of the previously constructed "Shanghanlun" database designed for comparison with other texts was applied for comparative analysis. Results : For input and analysis, 6 tables and 12 queries were made and used. Formulas were accessible by using herbal combinations, and applications of these formulas could be assembled for comparison. Formulas were also accessible by using disease pattern combinations, and combinations of herbs and disease pattern together were also applicable. In comparison with other texts, examples and frequency of usage of herbs could be relatively accurately compared, while disease patterns could not easily be compared. Conclusions : Herbal combinations, disease pattern combinations could yield related texts and herb/disease pattern combinations of the prescriptions in the "Jinguiyaolue", which shortened time needed for research among formulas in texts. However, standardization research for disease pattern is necessary for a more accurate comparative study that includes disease pattern information.

Evidence-Developing Disease Control of Coronavirus Disease 2019 (코로나19의 증거생성 질병관리)

  • Park, Eun-Cheol
    • Health Policy and Management
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    • v.30 no.4
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    • pp.431-432
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    • 2020
  • Coronavirus disease 2019 (COVID-19) has been going on for nearly a year. As of December 1, 2020, more than 60 million confirmed cases and 1.4 million deaths have occurred in 220 countries and territories. There is no effective treatment for COVID-19 so far, and vaccines are being developed. However, the vaccine of COVID-19 can be freed from COVID-19 only if there are positive answers to some questions: "Aren't there any major side effects from the vaccine?"; "Is the vaccine effective for enough time?"; "Does the vaccine sufficiently reduce the mortality rate?"; and "Does the vaccine sufficiently reduce the reproduction number?" The fight against COVID-19 will continue for a long time. Therefore, we need to respond by developing the evidence for control of COVID-19, the emerging infectious disease. Extensive quarantine measures in the early stages of COVID-19 need to be elaborated through developing the evidence. Korea Disease Control and Prevention Agency should establish a database for evidence developing COVID-19 control. In this database, based on more than 3 million tested individuals, epidemiological investigation results, health insurance claims data, and government data such as the Ministry of Public Administration and Security, etc. should be linked. It is necessary to disclose this database to academia, etc. to create the evidences of COVID-19 and manage COVID-19 through these. And through the developed evidences, guidelines for physical health and mental health in the era of Corona 19 should be developed.

Retrospective Drugs Utilization Review Study for Chronic Kidney Disease Using National Health Insurance Database (건강보험 자료를 이용한 만성신부전 환자의 신독성 약물사용 현황)

  • Kim, Dong-Sook;Lee, Hyun-Jeong;Son, In-Ja;Kim, Gui-Sook;Shin, Joo-Young;Lee, Kun-Sei
    • YAKHAK HOEJI
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    • v.53 no.3
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    • pp.138-144
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    • 2009
  • The purpose was to implement drug utilization review (DUR) for whom were diagnosed with chronic kidney disease (CKD) population using health insurance claim data. This study constructed drug utilization database using Health Insurance Review and Assessment Service (HIRA) database and selected contraindicated drugs with kidney based on previously developed drug utilization guide and reviewing other countries' examples. Main outcome measures were the proportion of prescription for 1 or more drugs of concern. The cohort included 115,948 subjects, who were diagnosed with chronic kidney disease. Inappropriate drugs with CKD patients was some used, and the most commonly prescribed classes were aluminum drugs. However it is difficult to find problems with inappropriate drug because claims data doesn't have laboratory data. Based on the result of retrospective drug utilization review study, more studies should be analysed drug utilization patterns and monitoring system should be developed.

Current Research Status of National Health Insurance Database Studies in Korea Related to Parkinson's Disease and Future Research Proposals for Integrative Therapies (국민건강보험공단 청구자료를 활용한 파킨슨병과 관련된 코호트 연구 디자인 분석 및 향후 한의중재 관련 파킨슨 후향적 코호트 연구를 위한 제언)

  • Ye-Chae Hwang;Jungtae Leem
    • Journal of Society of Preventive Korean Medicine
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    • v.28 no.1
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    • pp.69-87
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    • 2024
  • Objectives : This study is to investigate the current National Health Insurance Database cohort studies related to complications of Parkinson's Disease (PD) and suggest the design of Korean medical epidemiological studies of PD. Methods : Nationwide longitudinal studies of PD patients in South Korea were collected through Pubmed and the Korea Citation Index (KCI). We selected cohort studies that used the National Health Insurance Database in Korea and targeted Parkinson's disease patients. Studies published before February 2024 were categorized according to study designs. We examined variables and covariates, enroll dates and matching methods. Results : Of a total of 536 studies, 18 studies met the inclusion criteria. All studies used the National Health Insurance (NHI) Research Database and among them, 5 used sample data and one senior database. Studies can be classified into two types. 11 cohort studies were comparing PD patients and non-PD patients. Another type was 4 PD patients cohort studies. Most studies used two diagnostic codes (G20 and V124) for inclusion criteria. Enroll periods were from 2002 to 2017, and follow-up periods were from 7 to 14 years. 16 studies considered age and sex as covariates. 15 studies used the propensity score matching method to increase the level of causality. There was only one study related to the Korean medical treatment. Conclusion : In future cohort studies on Korean medical treatment, more attempts should be made to reveal the effect of the treatments on PD patients by defining inclusion criteria for patient groups, covariates, exposure variables, and assessment indicators more operatively.

Structural Bioinformatics Analysis of Disease-related Mutations

  • Park, Seong-Jin;Oh, Sang-Ho;Park, Dae-Ui;Bhak, Jong
    • Genomics & Informatics
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    • v.6 no.3
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    • pp.142-146
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    • 2008
  • In order to understand the protein functions that are related to disease, it is important to detect the correlation between amino acid mutations and disease. Many mutation studies about disease-related proteins have been carried out through molecular biology techniques, such as vector design, protein engineering, and protein crystallization. However, experimental protein mutation studies are time-consuming, be it in vivo or in vitro. We therefore performed a bioinformatic analysis of known disease-related mutations and their protein structure changes in order to analyze the correlation between mutation and disease. For this study, we selected 111 diseases that were related to 175 proteins from the PDB database and 710 mutations that were found in the protein structures. The mutations were acquired from the Human Gene Mutation Database (HGMD). We selected point mutations, excluding only insertions or deletions, for detecting structural changes. To detect a structural change by mutation, we analyzed not only the structural properties (distance of pocket and mutation, pocket size, surface size, and stability), but also the physico-chemical properties (weight, instability, isoelectric point (IEP), and GRAVY score) for the 710 mutations. We detected that the distance between the pocket and disease-related mutation lay within $20\;{\AA}$ (98.5%, 700 proteins). We found that there was no significant correlation between structural stability and disease-causing mutations or between hydrophobicity changes and critical mutations. For large-scale mutational analysis of disease-causing mutations, our bioinformatics approach, using 710 structural mutations, called "Structural Mutatomics," can help researchers to detect disease-specific mutations and to understand the biological functions of disease-related proteins.

Implementation and Application of Fish Drug Information System (어류 약물정보시스템의 구현 및 응용)

  • Kim, Hae-Ran;Park, Gae-Hwa;Cho, Hyug-Hyun;Ceong, Hee-Taek
    • The Journal of the Korea institute of electronic communication sciences
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    • v.2 no.2
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    • pp.92-98
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    • 2007
  • Database System of approved fish drug products was consisted of trade name, species, ingredients, sponsor, disease, dose forms, drug forms, indication, law and so on. Also in addition, we will develope the database system for fish disease information. So we propose to expand and practice for publishing a medical prescription and making an order of drug by Fish Disease Distinction System which is based on drug information system and disease information system.

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Diagnosis of Pet by Using FCM Clustering

  • Kim, Kwang-Baek
    • Journal of the Korea Society of Computer and Information
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    • v.26 no.2
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    • pp.39-44
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    • 2021
  • In this paper, we propose a method of disease diagnosis system that can diagnose the health status of household pets for the people who lack veterinary knowledge. The proposed diagnosis system holds 50 different kinds of diseases with the symptoms for each of them as a database to provide results from symptom input. Each disease database has its own symptom codes for a disease, and by using the disease database, FCM clustering technique is applied to disease which outputs membership degree to determine diseases close to the input symptom as a pet diagnosis result. The implementation results of the proposed pet diagnosis system were obtained by the number of selected symptoms and the possibility values of the diseases that have the selected symptoms being sorted in descending order to derive top 3 diseases closest to the pet's symptom.

CareMyDog: Pet Dog Disease Information System with PFCM Inference for Pre-diagnosis by Caregiver

  • Kim, Kwang Baek;Song, Doo Heon;Park, Hyun Jun
    • Journal of information and communication convergence engineering
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    • v.19 no.1
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    • pp.29-35
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    • 2021
  • While the population of pet dogs and pet-related markets are increasing, there is no convenient and reliable tool for pet health monitoring for pet owners/caregivers. In this paper, we propose a mobile platform-based pre-diagnosis system that pet owners can use for pre-diagnosis and obtaining information on coping strategies based on their observations of the pet dog's abnormal behavior. The proposed system constructs symptom-disease association databases for 100 frequently observed diseases under veterinarian guidance. Then, we apply the possibilistic fuzzy C-means algorithm to form the "probable disease" set and the "doubtable disease" set from the database. In the experiment, we found that the proposed system found almost all diseases correctly, with an average of 4.5 input symptoms and outputs 1.5 probable and one doubtable disease on average. The utility of this system is to alert the owner's attention to the pet dog's abnormal behavior and obtain an appropriate coping strategy before consult a veterinarian.

Object Detection-Based Cloud System: Efficient Disease Monitoring with Database (객체 검출 기반 클라우드 시스템 : 데이터베이스를 통한 효율적인 병해 모니터링)

  • Jongwook Si;Junyoung Kim;Sungyoung Kim
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.4
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    • pp.210-219
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    • 2023
  • The decline in the rural populace and an aging workforce have led to fatalities due to worsening environments and hazards within vinyl greenhouses. Therefore, it is necessary to automate crop cultivation and disease detection system in greenhouses to prevent labor loss. In this paper, an object detection-based model is used to detect diseased crop in greenhouses. In addition, the system proposed configures the environment of the artificial intelligence model in the cloud to ensure stability. The system captures images taken inside the vinyl greenhouse and stores them in a database, and then downloads the images to the cloud to perform inference based on Yolo-v4 for detection, generating JSON files for the results. Analyze this file and send it to the database for storage. From the experimental results, it was confirmed that disease detection through object detection showed high performance in real environments like vinyl greenhouses. It was also verified that efficient monitoring is possible through the database