• The Journal of the Korean life insurance medical association
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• v.27 no.1
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• pp.21-23
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• 2008

The 5th revision of Korean Classification of Diseases(KCD) became effective on January 1, 2008. It has reflected the changes made to the tenth revision of International Classification of Diseases (ICD-10) between 1998 and 2005 and the suggestions of academic and related societies in Korea. Two important alterations seem to have a major implication in the insurance industry. One would be the official introduction of a Korean version of International Classification of Diseases for Oncology, third edition(ICD-O-3). The borderline ovarian tumor is classified as a borderline neoplasm, which was classified as a malignant neoplasm in the previous edition of International Classification of Diseases for Oncology. The other would be the appearance of non-C-code malignant neoplasm for the diseases, such as polycythemia vera, newly classified as a malignant neoplasm by the current edition of International Classification of Diseases for Oncology. The National Office of Statistics(NSO) adopted the way of implementation used in the Australian Modification of International Classification of Diseases(ICD-10-AM), instead of assigning them into corresponding C code. Overall, the changes made in this revision doesn't seem to have a serious impact on the insurance industry since it has only reflected updates made to ICD-10.

• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.324-330
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• 2021

Agriculture is one of the essential needs of human life on planet Earth. It is the source of food and earnings for many individuals around the world. The economy of many countries is associated with the agriculture sector. Lots of diseases exist that attack various fruits and crops. Apple Tree Leaves also suffer different types of pathological conditions that affect their production. These pathological conditions include apple scab, cedar apple rust, or multiple diseases, etc. In this paper, an automatic detection framework based on deep learning is investigated for apple leaves disease classification. Different pre-trained models, VGG16, ResNetV2, InceptionV3, and MobileNetV2, are considered for transfer learning. A combination of parameters like learning rate, batch size, and optimizer is analyzed, and the best combination of ResNetV2 with Adam optimizer provided the best classification accuracy of 94%.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.4
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• pp.718-724
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• 2008

In order to classify diseases of oriental medicine in liaison with International Classification of Diseases, there should be intermediation and sharing concepts between the two in addition to proper classification. Classification units were settled for differentiation of diseases or syndromes first. And second, the standard forms of disease classification system were proposed. Third, this classification system was made of serial groupings of syndrome under the traditional disease name. Fourth, the location of disease and the interrelation between different syndromes were depicted with diagram in order to define more clearly. As the results and conclusion, The classification units were composed of 2 categories; topology, organ, meridian, somatic structure, body fluid units for description and various regulatory unit terms of western and traditional medicine for explanation. The mixed classification model of western diseases and traditional syndromes(證) was adopted as a fundamental classification system containing disease by exterior pathogen, systemic internal diseases, psychoneuronal diseases, metabolic diseases, diseases of sense organs, supportive structure diseases, obstetric-gynecology diseases, child diseases, 4-type constitutional diseases. And those were differentiated with generalized, localized, functional, oncogenic, environmental features in detail. The cause, site, condition, dispositions must be expressed in each disease name too. The types of diagnosis using classification system are principal and final diagnosis, principal procedure, main conditions, and these are applied to this Korean classification system equally. For more clarification of differentiation, a plane topological map and three dimensional coordinates were proposed to manifest the location, features and relation of disease itself or each other.

• Korean Journal of Veterinary Service
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• v.28 no.1
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• pp.49-69
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• 2005

More than 30 years have elapsed since the first report of the International Committee on Taxonomy of Viruses (ICTV) was published in 1971. Since that publication, the ICTV recognizes about 1,550 virus species, but some 30,000 virus strains and isolates are being tracked by virologists in different fields of biology. The ICTV is the 'international court' of experts that rules on names and relationships of all virus, but only to the level of species. Virus taxonomy is changing rapidly, with changes ranging from the trivial(use of italics for species names) to profound reorganization driven by the explosion of sequence information. The universal system of viral taxonomy now accepts Linnean-like classification at the levels of order, family, subfamily, genus, and species. The suffix '-virales' identifies an order, Families are identified by the suffix '-viridae' subfamilies are identified by the suffix '-virinae', and genera are identified by the suffix '-virus'. The importance of distinguishing subspecies, strains, and isolates in vaccine development, diagnostics, etc. is recognized, but these lower levels are not formally classified by ICTV. This paper mainly introduces taxonomy and classification of animal viruses on the basis of the seventh report of the ICTV edited by Van Regenmortal et al. in 2000.

• Journal of Physiology & Pathology in Korean Medicine
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• v.21 no.3
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• pp.776-780
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• 2007

Recently World Health Organization Western Pacific Regional Office (WHO/WPRO) has developed the WHO International Standard Terminologies on Traditional Medicine in the Western Pacific Region (IST), and is developing WHO International Classification of Traditional Medicine/Western Pacific Regional Office (ICTM/WPRO). Regarding ICTM, WHO/WPRO hoped that it will be incorporated to International Classification of Disease (ICD) 11$^{th}$ edition, published in 2015. The author reports the proceedings of these two standardizations on terminologies and diseases of traditional medicine in East Asia.

• Journal of Preventive Medicine and Public Health
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• v.32 no.4
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• pp.538-545
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• 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.

• Journal of Society of Preventive Korean Medicine
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• v.4 no.2
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• pp.93-107
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• 2000

Korea follows the Korea standard classification of disease and causes of death according to the ICD(international classification of disease) Oriental medicine began to of officially follow the classification of disease for using the Korean classification of diseases in 1972. The classification of OM(oriental medicine) has changed in shape experiencing two amendments. The largest difficulty was to overcome the different names of diseases between OM and ICD. A one-to-one correspondence of the name of a disease between OM and ICD is impossible So in the primary stage one-to-one and one-to-many correspondence was made. During the first amendment the international disease names were re-classified on the oriental medicine disease name's basis and at the same time the classification of OM was corresponded on a one-to-one basis to the ICD . During the second amendment this changed to many-to-many correspondence . Analyzing the history of classification of OM during the first and second amendments, it was discovered that establishment of the standards of classification, the unification of oriental medical terms, and overcoming the difference of disease names between the OM and ICD is necessary Also th classification and standardazation of OM must not stop as a single round. It must go on for a long time. The hosts of this project Korean oriental medical society and AKOM(association of korean oriental medicine) need to build a independant department which will supervise the classification project and monitor any problems to come up. Also a route through which suggestions can be taken in and new solutions can be brought up needs to be secured and an atmosphere in which studies can take place about the basis of classifications needs to be developed.

• Tuberculosis and Respiratory Diseases
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• v.78 no.3
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• pp.180-189
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• 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.

• Anxiety and mood
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• v.1 no.1
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• pp.18-24
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• 2005

The Diagnostic and Statistical Manual 4th edition (DSM-IV) has been widely accepted and used for international classification of mental disorder. The DSM has been changed to improve diagnostic reliability and validity through descriptive and categorical approaches which was undertaken atheoretically. The authors reviewed current studies about the DSM-IV classification system and the diagnostic issues of representative categories of anxiety disorder. The authors concluded that the anxiety disorder classification system in DSM-IV has limitations such as a lack of empirical consideration for overlapping features of anxiety disorders and a lack of discriminant validity. To improve diagnostic validity and revise the current DSM-IV classification system, the authors suggested 1) more longitudinal studies for collecting empirical evidence, 2) decreasing the dependence upon operational criteria, 3) deceasing diagnostic boundary blurring, 4) developing disease specific biological diagnostic techniques and 5) continued collaboration between the DSM and International Classification of Diseases (ICD) systems.

• Proceedings of the KSLP Conference
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• 2003.11a
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• pp.208-211
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• 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.