• 한국콘텐츠학회논문지
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• 제22권3호
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• pp.354-360
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• 2022

대사성 질환은 국내의 경우 유병률이 26%에 이르는 질환으로 복부비만, 고혈압, 공복혈당장애, 고중성지방, 낮은 HDL 콜레스테롤 5가지 상태 중 3가지를 동시에 가진 상태를 말한다. 본 논문은 농촌진흥청의 소비자패널 데이터와 건강보험공단의 진료 데이터를 연계하여 식품 소비 특성을 통해 대사성 질환자군과 대조군으로 나누는 분류 모델을 생성하고 차이를 비교하고자 한다. 기존의 국내외에서 연구된 많은 대사성 질환과 식품 소비 특성 관련 연구는 특정 식품군이나 특정 성분의 질환 상관성 연구이며, 본 논문은 일반 식사에서 포함하는 모든 식품군을 고려한 로지스틱 회귀를 이용한 분류 모델, 의사결정나무 기반 분류 모델, XGBoost를 활용한 분류 모델을 생성하였다. 세 가지 모델 중 정확도가 높은 모델은 XGBoost 분류 모델이지만, 정확도가 0.7 미만으로 높지 않았다. 향후 연구로 환자군의 식품 소비 관찰 기간을 5년 이상으로 확대하고 섭취한 식품을 영양적 특성으로 변환한 후 대사성 질환 분류 모델 연구가 필요하다.

• Pediatric Infection and Vaccine
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• 제18권1호
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• pp.54-60
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• 2011

목 적 : 소아청소년과에 입원하는 흔한 원인 질병을 조사하여, 기간별 연령군별 질병의 분포를 확인하고 그 역학적 변화를 추정하기 위하여 본 연구를 계획하였다. 방 법: 1997년부터 2008년까지 소아청소년과 입원환자를 대상으로, 인구학적 특징, 입원일, 질병코드(ICD-10)를 조사하였다. 연구 기간은 전반기(1997-2002)와 후반기(2003-2008)로 양분하였고, 연령은 영아기, 유아기, 학령기 및 청소년기, 4군으로 구분하여 다빈도 질병을 비교하였다. 결 과: 12년간 입원 환자수는 총 33,513명이었다. 다빈도 질병은 폐렴(J12-J18; 21.2%), 장염(A00-A09; 17.8%), 모세기관지염(J21; 11.9%) 등 순이었고, 1-10위 다빈도 질병은 전체의 79.1%를 차지하였다. 기간별 비교에서 호흡기 감염질환(모세기관지염, 중이염, 부비동염)과 림프절 종대, 농가진/봉와직염으로 입원한 환자수는 증가하였고 무균 수막염, 장중첩증, 홍역, 신증후군/신염으로 입원한 환자수는 감소하였다. 연령군별로 다빈도 질병의 분포에 차이를 보이기도 하여서 질병에 따른 호발 연령군을 확인하였다. 결 론:다빈도 질병은 기간별 연령군별로 차이를 보였다. 이러한 역학적 변화는 소아청소년과의 진료계획 수립에 반영되어야 할 것이다.

• 한국컴퓨터정보학회논문지
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• 제23권12호
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• pp.43-48
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• 2018

In this paper, more efficient classification result could be obtained by applying the combination of the Hidden Markov Model and SVM Model to HMSV algorithm gene expression data which simulated the stochastic flow of gene data and clustering it. In this paper, we verified the HMSV algorithm that combines independently learned algorithms. To prove that this paper is superior to other papers, we tested the sensitivity and specificity of the most commonly used classification criteria. As a result, the K-means is 71% and the SOM is 68%. The proposed HMSV algorithm is 85%. These results are stable and high. It can be seen that this is better classified than using a general classification algorithm. The algorithm proposed in this paper is a stochastic modeling of the generation process of the characteristics included in the signal, and a good recognition rate can be obtained with a small amount of calculation, so it will be useful to study the relationship with diseases by showing fast and effective performance improvement with an algorithm that clusters nodes by simulating the stochastic flow of Gene Data through data mining of BigData.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2007년도 심포지엄 논문집 정보 및 제어부문
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• pp.101-102
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• 2007

Heart diseases are critical and should be detected as soon as possible. A stethoscope is a simple device to find cardiac disorder but requires keen experiences in heart sounds. We evaluate a cardiac disorder classifier by using heart sounds recorded by a digital wireless stethoscope developed in this work. The classifier uses hidden Markov models with circular state transition to model the heart sounds. We train the classifier using two kinds of data: One recorded by using our stethoscope and the other sampled from a clean heart sound database. In classification experiments using 165 sound clips, the classifier shows the classification accuracy of 82% in classifying 6 cardiac disorder categories.

• Journal of Veterinary Science
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• 제21권2호
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• pp.19.1-19.10
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• 2020

Given that the current Newcastle disease virus (NDV) infection in wild birds poses the threat to poultry, surveillance of Newcastle disease in captive wild birds was carried out in Jilin, China in 2018. Here, an NDV strain obtained from toco toucan was firstly characterized. The results showed that the F gene of the NDV isolate Toucan/China/3/2018 is classified as genotype II in class II. Sequence analysis of the F0 cleavage site was ¹¹³RQGR/L¹¹⁷, which supports the result of the intracerebral pathogenicity index assay indicating classification of the isolate as low-pathogenicity. Experimental infection demonstrated that Toucan/China/3/2018 can effectively replicate and transmit among chickens. To our knowledge, this is the first report on genetically and pathogenically characterizing NDV strain isolated from toucan, which enriches the epidemiological information of NDV in wild birds.

• Journal of Acupuncture Research
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• 제33권1호
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• pp.69-77
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• 2016

Objectives : The objective of this study is to review external approaches using acupuncture and related treatments of hyperpigmentation disorders and their classification in traditional medicine. Methods and Results : Hyperpigmentation was recorded for the first time in Treatise on the Pathogenesis and Manifestations of All Diseases published in 610 A.D. This suggests that the symptom has already been recognized as an independent disease in East Asia for more than 1,400 years. Over the course of several centuries, there has been a significant evolution in the traditional treatments for hyperpigmentation. There are many different types of therapy, including body acupuncture, intradermal acupuncture, ear acupuncture, ear acupressure, blood-letting treatment, pharmacopuncture, plum-blossom needle therapy, burning acupuncture therapy, moxibustion, and guasha. In addition, the traditional classification of hyperpigmentation has been changing shape. However, no attempts have been made to establish the academic linkage between the modern classification of hyperpigmentation disorders and the traditional one, on account of different concepts and names of the ailment. This study was designed in an attempt to identify the linkage of the categorization of the Korean Standard Classification of Disease (KCD) and the traditional classification. Conclusions : Through this literature review, we found that there has been a significant evolution in the treatment of hyperpigmentation disorders in East Asia. Traditional medical treatment for skin disease, including hyperpigmentation, is expected to be further developed with the advancement of science and technology.

• Tuberculosis and Respiratory Diseases
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• 제82권4호
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• pp.269-276
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• 2019

Idiopathic interstitial pneumonia (IIP) is a histologically identifiable pulmonary disease without a known cause that usually infiltrates the lung interstitium. IIP is largely classified into idiopathic pulmonary fibrosis, idiopathic non-specific interstitial pneumonia, respiratory bronchiolitis-interstitial lung disease (ILD), cryptogenic organizing pneumonia, desquamative interstitial pneumonia, and acute interstitial pneumonia. Each of these diseases has a different prognosis and requires specific treatment, and a multidisciplinary approach that combines chest high-resolution computed tomography (HRCT), histological findings, and clinical findings is necessary for their diagnosis. Diagnosis of IIP is made based on clinical presentation, chest HRCT findings, results of pulmonary function tests, and histological findings. For histological diagnosis, video-assisted thoracoscopic biopsy and transbronchial lung biopsy are used. In order to identify ILD associated with connective tissue disease, autoimmune antibody tests may also be necessary. Many biomarkers associated with disease prognosis have been recently discovered, and future research on their clinical significance is necessary. The diagnosis of ILD is difficult because patterns of ILD are both complicated and variable. Therefore, as with other diseases, accurate history taking and meticulous physical examination are crucial.

• 대한음성학회지:말소리
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• 제45호
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• pp.35-45
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• 2003

Laryngeal diseases cause significant changes in the quality of speech production. Automatic detection of laryngeal diseases by voice is attractive because of its nonintrusive nature. In this paper, we apply speech recognition techniques to detection of laryngeal cancer, and investigate which feature parameters and classification methods are appropriate for this purpose. Linear Predictive Cepstral Coefficients (LPCC) and Mel-Frequency Cepstral Coefficients (MFCC) are examined as feature parameters, and parameters reflecting the periodicity of speech and its perturbation are also considered. As for classifier, multilayer perceptron neural networks and Gaussian Mixture Models (GMM) are employed. According to our experiments, higher order LPCC with the periodic information parameters yields the best performance.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2017년도 추계학술대회
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• pp.405-407
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• 2017

The environmental change is affecting the farm products like tomato, and pepper, etc. This affects to lead smart farming yield. What is more, this inconstant conditions cause the farms to be infected by variety diseases. Therefore ICT technology is needed to detect and prevent the crops from being effected by diseases. This article suggests the procedure to help producer for identifying farms disease based on the detected image. This detects the kind of diseases with comparing the trained image data before and after disease emergence. First step monitors an image of farms and resize it. Its features are extracted on parameters such as color, and morphology, etc. The next steps are used for classification to classify the image as infected or non-infected. on the bassis of detection algorithm.

• 농촌의학ㆍ지역보건
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• 제13권1호
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• pp.32-40
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• 1988

Anisakiasis occur after the ingestion of raw marine fish and squid containg anisakid larvae. In recent years about 40 cases of anisakiasis have been recorded in Korea. Considering, however, the Korean style of eating raw fish, many more cases would exist and prevention is necessary. We describe the infection rate of anisakid larvae in 13 species of marine fish and squid which were caught in the Korean sea. And each extracted larva is classified according to morphological characters. The results are following ; Scomber japonicus, Pseudosciaena manchurica, Trichiurus haumela showed high infection rate of anisakid larvae. Although Sepia esculenta showed low infection rate, most of anisakid larvae found in Sepia edulis are embedded in muscles. So relative high frequent rate of anisakiasis may developed by Sepia esculenta. Five type (Anisakis Type I, Terranova Type B, Raphidascaris sp., Contracaecum Type A, Contracaecum Type D) of anisakid larvae are classified according to their morphological characters.