• Tuberculosis and Respiratory Diseases
• /
• 제81권4호
• /
• pp.347-348
• /
• 2018

• 대한치과의사협회지
• /
• 제48권6호
• /
• pp.459-468
• /
• 2010

International Classification of Disease (ICD-10) is widely used as a crucial reference not only in the medical diagnosis of diseases but also within the health insurance system. It makes possible for medical personnel to make decisions systematically and for the people working in the health insurance or public health industries to better understand medical issues. However, this classification is often not enough or acceptable in a clinical setting. Many countries amend in their own way to make it more appropriate for their people. Korean Classification of Disease (KCD-5) was made by adding a 5 digit code for some diseases to clarify the conditions of the patients. The authors found problems of KCD-5 in temporomandibular disorders and several related medical problems. Medical treatment for these problems had not been covered even by public health insurance until 2000 in Korea. For the last decade, private insurance companies have introduced new items for reimbursement of the treatment fees the patients actually pay. The authors assumed that many patients with these medical problems encountered difficulties in the reimbursement from private insurance companies because KCD-5 did not classify these medical conditions appropriately. An overview of KCD-5 and suggestions for improvement are introduced in this study.

• Journal of Preventive Medicine and Public Health
• /
• 제31권3호
• /
• pp.540-563
• /
• 1998

This Study has been carried out to make a recommendation for the next amendment of the Infectious Disease Prevention Act with a specific focus on the kind of notifyable disease. Korean, Japanese, German, U.S, English and French acts on infectious diseases prevention were reviewed, compared with and analized in regards of numbers and kinds of notifyable infectious diseases and their tendency of amendments. An criteria was designed to assess the level of validity of diseases to be designated in the act. Four items, the fatality (greater than 10% or not), the possibility to make a big epidemic, the availability of efficient vaccination and the usefulness of isolation, are used in the assessment. This index is applied to the diseases in Korean and other countries' Infectious Disease Prevention Acts. Results are as follows: 1. The Korean Infectious Disease Preventon Act has a unique way of classifying the notifyable infectious disease, that is, the first, the second and the third class. But the author cannot find the basis of classification. No other countries reviewed have the similar classification. 2. The ten diseases, cholera, plague, yellow fever, diphtheria, typhoid fever, poliomyelitis, rabies, tetanus, malaria, and meningococcal meningitis are designated as the notifyable diseases not only in Korea but also in Japan, Germany, United States, England and france. 3. Thirty seven diseases including small pox, Lassa fever, anthrax, influenza, German measles, Legionellosis, infection with E. coli O157:H7, Q-fever, brucellosis, Lyme disease are designated as legal disease at least one of the above mentioned countries. 4. The Korea has been coped with the change of the infectious disease occurrence for last fifty years in amendment of the Infectious Disease Prevention Act. 5. Japan has a special infectious surveillance system composed of 3,880 clinics throughout the whole country. 6. Germany has classified infectious diseases in five categories which are based on seriousness of disease. Any confirmed death, cases and suspected cases in class I should be reported within 24 hours. But only confirmed death and cases in class II, but not suspected cases, are reportable in Germarny. 7. Plague, bacillary dysentery, pertussis, mumps, Japanese encephaltis and Korean hemorrhagic fevers are diseases with high credits validity index among Korean legal disease. 8. German measles, anthrax, E. coli O157 : H7 infection, Lassa fever, Q-fever, brucellosis are high in validity index among those which are not designated in Korea but designated in other countries. In conclusion, the Korean Infectious Disease Prevention Act has well been coped with the changes of infectious disease occurrence for last fifty years, but the classification basis and the validity of diseases to be designated as legal diseases is worth reevaluating.

• 한국환경과학회지
• /
• 제19권6호
• /
• pp.715-735
• /
• 2010

This study is designed to assess the priority order of the chemicals to cause to generate occupational diseases in order to understand the fundamental data required for the preparation of health protective measure for the workers dealing with chemicals. The 41 types of 51 ones of chemicals to cause to generate the national occupational diseases were selected as the study objects by understanding their domestic use or not, and their occupational diseases' occurrence or not among 110,608 types of domestic and overseas chemicals. To assess their priority order the sum of scores was acquired by understanding the actually classified condition based on a perfect score of physical riskiness(90points) and health toxicity(92points) as a classification standard by GHS, the priority order on GHS riskiness assessment, GHS toxicity assessment, GHS toxic xriskiness assessment(sum of riskiness plus toxicity) was assessed by multiplying each result by each weight of occupational disease's occurrence. The high ranking 5 items of chemicals for GHS riskiness assessment were turned out to be urethane, copper, chlorine, manganese, and thiomersal by order. Besides as a result of GHS toxicity assessment the top fives were assessed to be aluminum, iron oxide, manganese, copper, and cadium(Metal) by order. On the other hand, GHS toxicity riskiness assessment showed that the top fives were assessed to be copper, urethane, iron oxide, chlorine and phenanthrene by order. As there is no material or many uncertain details for physical riskiness or health toxicity by GHS classification though such materials caused to generate the national occupational diseases, it is very urgent to prepare its countermeasure based on the forementioned in order to protect the workers handling or being exposed to chemicals from health.

• 전기학회논문지
• /
• 제57권6호
• /
• pp.1058-1062
• /
• 2008

In clinical decision support system(CDSS), unlike rule-based expert method, appropriate data-driven machine learning method can easily provide the information of individual feature(clinical test) for disease classification. However, currently developed methods focus on the improvement of the classification accuracy for diagnosis. With the analysis of feature importance in classification, one may infer the novel clinical test sets which highly differentiate the specific diseases or disease states. In this background, we introduce a novel CDSS that integrate a classifier and feature selection module together. Random forest algorithm is applied for the classifier and the feature importance measure. The system selects the significant clinical tests discriminating the diseases by examining the classification error during backward elimination of the features. The superior performance of random forest algorithm in clinical classification was assessed against artificial neural network and decision tree algorithm by using breast cancer, diabetes and heart disease data in UCI Machine Learning Repository. The test with the same data sets shows that the proposed system can successfully select the significant clinical test set for each disease.

• Journal of Preventive Medicine and Public Health
• /
• 제32권4호
• /
• pp.538-545
• /
• 1999

Objective : To compare the predictive power of International Classification of Diseases 10th Edition(ICD-10) based International Classification of Diseases based Injury Severity Score(ICISS) with Trauma and Injury Severity Score(TRISS) and International Classification of Diseases 9th Edition Clinical Modification(ICD-9CM) based ICISS in the injury severity measure. Methods : ICD-10 version of Survival Risk Ratios(SRRs) was derived from 47,750 trauma patients from 35 Emergency Centers for 1 year. The predictive power of TRISS, the ICD-9CM based ICISS and ICD-10 based ICISS were compared in a group of 367 severely injured patients admitted to two university hospitals. The predictive power was compared by using the measures of discrimination(disparity, sensitivity, specificity, misclassification rates, and ROC curve analysis) and calibration(Hosmer-Lemeshow goodness-of-fit statistics), all calculated by logistic regression procedure. Results : ICD-10 based ICISS showed a lower performance than TRISS and ICD-9CM based ICISS. When age and Revised Trauma Score(RTS) were incorporated into the survival probability model, however, ICD-10 based ICISS full model showed a similar predictive power compared with TRISS and ICD-9CM based ICISS full model. ICD-10 based ICISS had some disadvantages in predicting outcomes among patients with intracranial injuries. However, such weakness was largely compensated by incorporating age and RTS in the model. Conclusions : The ICISS methodology can be extended to ICD-10 horizon as a standard injury severity measure in the place of TRISS, especially when age and RTS were incorporated in the model. In patients with intracranial injuries, the predictive power of ICD-10 based ICISS was relatively low because of differences in the classifying system between ICD-10 and ICD-9CM.

• 대한음성언어의학회:학술대회논문집
• /
• 대한음성언어의학회 2003년도 제19회 학술대회
• /
• pp.208-211
• /
• 2003

This paper introduces a history and achievements of the research activities on screening of laryngeal diseases using acoustic analysis. First domestic and international research trends are introduced. Next brief introduction of the research results by the authors are mentioned. First, classification method of the laryngeal diseases using neural network is summarized. Then similar research using ARS (Automatic Response System) is mentioned. Finally, current research activities on screening of laryngeal diseases on internet is introduced.

• Tuberculosis and Respiratory Diseases
• /
• 제78권3호
• /
• pp.180-189
• /
• 2015

Accurate lymph node staging of lung cancer is crucial in determining optimal treatment plans and predicting patient outcome. Currently used lymph node maps have been reconciled to the internationally accepted International Association for the Study of Lung Cancer (IASLC) map published in the seventh edition of TNM classification system of malignant tumours. This article provides computed tomographic illustrations of the IASLC nodal map, to facilitate its application in day-to-day clinical practice in order to increase the appropriate classification in lung cancer staging.

• 동의생리병리학회지
• /
• 제18권2호
• /
• pp.359-370
• /
• 2004

Before the current western medicine was spreaded out in the world as the main stream, each country had treated diseases with the medicine of their own and the traditional medical books, which are so characteristic, are handed down. Considering the earnest assignment to do in Korean medical of this age and one of the tendencies of medical circles in the world is putting together the current medicine with the traditional medicine, the production and spread of the classification system for the technical books which is contained the characteristic of traditional chinese medicine, the present condition of modern chinese medicine, and the future of it, must be settled without delay. The classification system for oriental medicine section developed in the range of the simple system before the time of flowering, since then the western medicine had grew as the main current in medicine in Korea. But until now the rational and realistic classification system based on the changeable time isn't be established, so setting up one of the classification systems for medicine section, it is classified according to the principle of classification system for medicine section. Hereupon, the result was made after researching the changes of modern classification system for korean and studying on the changes of classification system for oriental medicine section of the Korean decimal classification.

• 스마트미디어저널
• /
• 제9권1호
• /
• pp.16-22
• /
• 2020

본 연구에서는 Multi-Tasking U-net를 사용하여 영역 세분화 작업(Segmentation) 과 분류 작업(Classification) 이 동시에 수행되게 함으로써 파프리카 병과 충 진단을 수행하였다. 시설 농장의 파프리카에는 병의 종류가 다양하지 않다. 이 연구에서는 비교적 발생빈도가 높은 흰가루병과 응애에 의한 피해, 정상 잎 3개의 클래스에 대해서만 진단 할 수 있도록 하였다. 이를 위한 중추 모델로는 U-net을 사용하였다. 또, 이 모델의 Encoder와 Decoder의 최종 단을 활용하여 분류 작업과 영역 세분화 작업이 각 각 수행되게하여, U-net의 Encoder가 분류작업과 영역 세분화 작업에 공유되도록 하였다. 학습 데이터로는 정상 잎 680장, 응애에 의한 피해 잎 450장, 흰가루병 370장을 사용하였다. 테스트 데이터로는 정상 잎 130장, 응애에 의한 피해 잎 100장, 흰가루병 90장을 사용하였고, 이를 통한 테스트 결과로는 89%의 인식률을 얻었다.