• The Korean Journal of Applied Statistics
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• v.19 no.1
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• pp.183-193
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• 2006

We consider a new classification method(DnDclass) combining two classification rules based on $L_1$-distance(L1DISTclass) and $L_1$-data depth(L1DDclass). To investigate characteristics and to evaluate the performance of these classification methods, we use simulation data in various settings. Through this simulation study, we can confirm that the new method, DnDclass, performs relatively well in many cases.

• Journal of Sasang Constitutional Medicine
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• v.14 no.3
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• pp.74-84
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• 2002

The purpose of study is 584 patients who had been treated in the Oriental Medical Hospital at Dong Eui Medical Center during 1 year from February 2001 to January 2002. We proceeded the judgment of Sasang constitution by 'Questiinaire of Sasang Constitution Classification(I)' and 'Questiinaire of Sasang Constitution Classification II(QSCCII)'. The following conclusion were made in comparison with Sasang Constitution and Questiinaire about disease and style of symptoms. 1. The subject of 'increase of the weight of a body(gain weight), cough, nasal discharge(rhinorrhea), stuffed nose, sweatier, more like fat food, more like salty food', has significant differences in sasang constitution classification. The frequency of Taeum group is more than of Soeum group and Soyang group. 2. The subject of 'the complextion is bad, anorexia, indigestion, nervousness, sonitus', has significant differences in sasang constitution classification. The frequency of Soeum group is more than of Taeum group and Soyang group. 3. The subject of 'urodynia, otic discharge', has significant differences in sasang constitution classification. The frequency of Soyang group is more than of Taeum group and Soeum group.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.3
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• pp.540-547
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• 2009

There needs disease-predictable signs in order to enable preventive diagnosis and therapy. Then traditional Chinese medicine applies various medical diagnostic equipments used in western medicine to diagnosing sub-healthy state. But such data are not originated from inherent oriental medicine, and not obtained easily in ordinary clinical practice. This paper is to provide synopsis of the ante-disease diagno-therapeutics partly and to show predictable data based on the facial shapes and signs, especially of gall bladder's versus bladder's body and masculine versus feminine shape. Ante-disease means not only the complete healthy state, but also the state unseen any symptoms in macrographically in the course of outbreak of disease. It contains two stages, first one is the former state of disease and second one is untransmitted state of disease. The patterns of ante-disease consist of latent disease, pre-disease, transmission type like senescent syndrome, abnormal reactive syndrome(變證), syndrome of transmission and transmutation. The classification with gall bladder and bladder type manifests the differences of shape, color and size of each organ in comparison of the universal and standard figures of the human being. On the other hand, the classification with masculine and feminine shape contrasts the innate sexual difference and the shape, characteristics originated from in itself. These two classification theories have their own pathologic types and syndrome types with each disease so that disease-predictable data can be constructed based on such a relationship. In addition, this diagnostic method by facial shapes and signs is able to be applied to whole stages from prenatal to present state of disease even if the cause and inducement are not clear. Ante-disease diagno-theraputic system by Gall Bladder's versus Bladder's Body and Masculine versus Feminine Shape is getting more important in the chronic and internal disease in comparison of the acute and traumatic disease. So this study is able to make up for the limit of diagnosis on ante-disease in the field of oriental medicine clinic.

• Journal of Korea Multimedia Society
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• v.22 no.10
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• pp.1168-1177
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• 2019

In order to diagnose and prevent Alzheimer's Disease (AD), it is becoming increasingly important to develop a CAD(Computer-aided Diagnosis) system for AD diagnosis, which provides effective treatment for patients by analyzing 3D MRI images. It is essential to apply powerful deep learning algorithms in order to automatically classify stages of Alzheimer's Disease and to develop a Alzheimer's Disease support diagnosis system that has the function of detecting hippocampus and CSF(Cerebrospinal fluid) which are important biomarkers in diagnosis of Alzheimer's Disease. In this paper, for AD diagnosis, we classify a given MRI data into three categories of AD, mild cognitive impairment, and normal control according by applying 3D brain MRI image to the Faster R-CNN model and detect hippocampus and CSF in MRI image. To do this, we use the 2D MRI slice images extracted from the 3D MRI data of the Faster R-CNN, and perform the widely used majority voting algorithm on the resulting bounding box labels for classification. To verify the proposed method, we used the public ADNI data set, which is the standard brain MRI database. Experimental results show that the proposed method achieves impressive classification performance compared with other state-of-the-art methods.

• Journal of the Korean Society for information Management
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• v.35 no.2
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• pp.63-88
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• 2018

This research evaluated differences of classification performance for feature selection methods using LDA topic model and Doc2Vec which is based on word embedding using deep learning, feature corpus sizes and classification algorithms. In addition to find the feature corpus with high performance of classification, an experiment was conducted using feature corpus was composed differently according to the location of the document and by adjusting the size of the feature corpus. Conclusionally, in the experiments using deep learning evaluate training frequency and specifically considered information for context inference. This study constructed biomedical document dataset, Disease-35083 which consisted biomedical scholarly documents provided by PMC and categorized by the disease category. Throughout the study this research verifies which type and size of feature corpus produces the highest performance and, also suggests some feature corpus which carry an extensibility to specific feature by displaying efficiency during the training time. Additionally, this research compares the differences between deep learning and existing method and suggests an appropriate method by classification environment.

• Speech Sciences
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• v.8 no.2
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• pp.61-71
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• 2001

Speech material, which is collected from ARS(Automatic Response System), was analyzed and classified into disease and non-disease state. The material include 11 different kinds of diseases. Along with ARS speech, DAT(Digital Audio Tape) speech is collected in parallel to give the bench mark. To analyze speech material, analysis tools, which is developed local laboratory, are used to provide an improved and robust performance to the obtained parameters. To classify speech into disease and non-disease class, multi-layered neural network was used. Three different combinations of 3, 6, 12 parameters are tested to obtain the proper network size and to find the best performance. From the experiment, the classification rate of 92.5% was obtained.

• Korean Journal of Agricultural Science
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• v.39 no.1
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• pp.117-123
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• 2012

Pathogenic fungi and bacteria such as Pectobacterium atrosepticum, Clavibacter michiganensis subsp. sepedonicus, Verticillium albo-atrum, and Rhizoctonia solani were the major microorganism which causes diseases in seed potato during postharvest process. Current detection method for disease-infected seed potato relies on human inspection, which is subjective, inaccurate and labor-intensive method. In this study, a reflectance spectroscopy was used to classify sound and disease-infected seed potatoes with the spectral range from 400 to 1100 nm. Partial least square discriminant analysis (PLS-DA) with various preprocessing methods was used to investigate the feasibility of classification between sound and disease-infected seed potatoes. The classification accuracy was above 97 % for discriminating disease seed potatoes from sound ones. The results show that Vis/NIR reflectance method has good potential for non-destructive sorting for disease-infected seed potatoes.

• Journal of Yeungnam Medical Science
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• v.38 no.1
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• pp.10-18
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• 2021

Endometriosis is a chronic disease associated with pelvic pain and infertility. Several classification systems for the severity of endometriosis have been proposed. Of these, the revised American Society for Reproductive Medicine classification is the most well-known. The ENZIAN classification was developed to classify deep infiltrating endometriosis and focused on the retroperitoneal structures. The endometriosis fertility index was developed to predict the fertility outcomes in patients who underwent surgery for endometriosis. Finally, the American Association of Gynecological Laparoscopists classification is currently being developed, for which 30 endometriosis experts are analyzing and researching data by assigning scores to categories considered important; however, it has not yet been fully validated and published. Currently, none of the classification systems are considered the gold standard. In this article, we review the classification systems, identify their pros and cons, and discuss what improvements need to be made to each system in the future.

• Journal of Preventive Medicine and Public Health
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• v.31 no.3 s.62
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• pp.540-563
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• 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.

• Journal of Sasang Constitutional Medicine
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• v.20 no.3
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• pp.51-57
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• 2008

1. Objective This study aims to establish the concept and classification of the Janggyeol(藏結) pathology introduced in the Sasang Constitutional Medicine literature. 2. Methods Different editions of Dongui suse bowon, including the Gabo version and the Sinchuk version, were compared for differences and similarities in the concept, symptomology, pathology, and therapeutics concerning the Soeumin Janggyeol disease. 3. Results and Conclusion (1) In the Gabo edition, Janggyeol(藏結) is introduced in the "Soeumin Interior Stomach Disease" section and the "Soeumin Summaries" section. However, instead of being included in the interior-based pathology, it is proposed as an independent disease category that is similar to and yet separate from the Taeeumbyeong Simhabiman (epigastric congestion) variations of Sugyeolhyung and Hansilgyeolhyung. Further, passages from the "Soyangin Summaries" section outline the underlying pathology in detail to show that this symptomatic pattern can be included in the exterior-based pathology. (2) In the Sinchuk edition, Janggyeol(藏結) is introduced in the "Soeumin Cold-based Stomach Interior-Cold Disease" section. Similarly to the Gabo classification, it is proposed as an independent disease category not necessarily included in the interior-based pathology that can be compared to the Taeeumbyeong Simhabiman(太陰人 心下 滿) category. The detailed pathological explanations in the "Soyangin Summaries" section suggest that this disease pattern is included in the exterior-based pathology. (3) Janggyeol(藏結) can be understood as a Taeyangbyeong Wigasil(太陽病胃家實) pathology in the Gabo edition and as a Taeyangbyeong Wigasil(太陽病胃家實) pathology in the Sinchuk edition.