• 사상체질의학회지
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• 제23권3호
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• pp.361-373
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• 2011

1. Objectives: The purpose of this study was done to learn the Sasang constitutional distribution and to find out if there are differences in the type of diseases and symptoms according to the Sasang constitution in Japan. 2. Methods: We collected data from 366 patients who visited the Department of Oriental Medicine, Keio University and recruited 132 healthy persons in Tokyo, Japan. For sasang constitution diagnosis, they all have done SSCQ-P(Sasang Constitution Questionaire for Patients) questionnaire. and a sasang constitution specialist diagnosed the sasang constitution of them. And We classify the diseases and symptoms of 313 patients according to KCD(Korean Standard Classification of Diseases) and learn the prevalences of diseases and symptoms according to Sasang Constitution. 3. Results: 1) Among the total 498 subjects, distributional rate of Taeyangin, Soyangin, Taeeumin, and Soeumin were 2.0%, 26.3%, 29.9%, and 41.8%. Among the 366 patients, distributional rate of Taeyangin, Soyangin, Taeumin, and Soeumin were 0.8%, 27.3%, 28.7%, and 43.2%. Among the 132 healthy group, distributional rate of Taeyangin, Soyangin, Taeeumin, and Soeumin were 5.3%, 23.5%, 33.3%, and 37.9%. 2) The prevalences of 'V.Mental and behavioural disorders', 'XI.Diseases of the digestive system', 'XV.Pregnancy, childbirth and the puerperium' and 'feeling of coldness(X VIII.Symptoms, signs and abnormal clinical and laboratory findings, NEC)' of Soeumin were significantly higher than those of the other constitutions.(p-value<0.05) 4. Conclusions: The distributional rate of Sasangin of Japanese was different from that of Korean and especially the distributional rate of Soeumin of Japanese was significantly higher than that of Korean. There were significant differences on the prevalences of some diseases and symtoms according to KCD in Soeumin.

• 한국방사선학회논문지
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• 제15권4호
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• pp.455-461
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• 2021

심장비대증은 흉부 X선 영상에서 흔히 보이는 질병 중 하나이지만 조기에 발견을 하지 못하면 심각한 합병증을 유발할 수도 있다. 이러한 점을 고려하여 최근에는 여러 과학기술 분야의 발전으로 인공지능을 이용한 딥러닝 알고리즘을 의료에 접목시키는 영상 분석 연구들이 많이 진행되고 있다. 본 논문에서는 Inception V3 딥러닝 모델을 흉부 X선 영상을 이용하여 심장비대증의 분류에 유용한 모델인지 평가하고자 한다. 사용된 영상의 경우 총 1026장의 경북대학교병원 내 정상 심장 진단을 받은 환자와 심장비대증 진단을 받은 환자의 흉부 X선 영상을 사용하였다. 실험결과 Inception V3 딥러닝 모델의 심장비대증 유무에 따른 분류 정확도와 손실도 결과값은 각각 96.0%, 0.22%의 결과값을 나타내었다. 연구결과를 통해 Inception V3 딥러닝 모델은 흉부 영상 데이터의 특징 추출 및 분류에 있어 우수한 딥러닝 모델인 것을 알 수 있었다. Inception V3 딥러닝 모델의 경우 흉부 질환의 분류에 있어 유용한 딥러닝 모델이 될 것으로 판단되며 조금 더 다양한 의료 영상 데이터를 이용한 연구를 진행하여 이와 같은 우수한 연구결과를 얻게 된다면 향후 임상의의 진단 시 많은 도움을 줄 수 있을 것으로 사료된다.

• 한국산업보건학회지
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• 제23권3호
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• pp.287-298
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• 2013

Objectives: Workers who use chemicals are exposed to safety accidents and occupational diseases. Employers are required to provide workers with Material Safety Data Sheets (MSDSs) in order to prevent accidents and diseases related to chemicals. Thus, it is very important to offer reliable MSDSs. In this paper, we assessed the reliability of MSDSs for chemicals including formaldehyde. Methods: To evaluate MSDS reliability, we collected 14 MSDSs and bulk samples from the chemical industry. MSDS reliability was evaluated by the completeness of details. In order to evaluate the adequacy of the formaldehyde contents in a mixture, bulk samples were collected and analyzed by HPLC. The result of Globally Harmonized System (GHS) classification was confirmed by identifying physical chemical properties, toxicology information and ecological information. Results: The result of the evaluation of 14 MSDSs showed 76.29% average reliability on each item, especially 53.9% average appropriate rate on hazard risk classification. No chemicals failed to match between the content (%) in MSDSs and the result of analysis. Conclusions: To elevate MSDSs reliability, the certified education of MSDS drafters and reorganization of the MSDS circulation system is required.

• 한국지능시스템학회논문지
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• 제22권6호
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• pp.786-792
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• 2012

마이크로어레이는 수만 가지 이상의 DNA 또는 RNA를 기판위에 배열해 놓은 것이며 이 기술을 이용하여 대량의 유전자 발현을 탐색할 수 있게 되었다. 그렇지만 마이크로어레이는 실험자가 탐색하려는 특정 표현형에 대해서 설계된 실험방법을 이용하므로 제한된 숫자의 유전자 발현만을 관찰할 수 있다. 본 논문에서는 MicroRNAs(miRNAs)와 Protein-Protein Interaction(PPI) 정보를 포함하고 있는 데이터베이스를 활용하여 마이크로어레이 데이터의 의미적 확장 방법을 제시하고자 한다. 또한 Online Mendelian Inheritance in Man(OMIM) 및 International Statistical Classification of Diseases and Related Health Problems, $10^{th}$ Revision(ICD-10)을 이용하여 질병 간 유전적 공통점 파악을 시도하였다. 이러한 접근방법을 통하여 새로운 생물학적 시각을 제공할 수 있을 것으로 기대된다.

• Journal of Veterinary Science
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• 제19권6호
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• pp.725-734
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• 2018

Ovaries of 21 bitches presented with gynecopathies were surgically removed and histologically examined. Standard histological, as well as immunohistochemical, classification of 193 cystic structures resulted in the classification of 72 cysts of subsurface epithelial structures (SES), 61 follicular cysts (FCs), 38 cystic rete ovarii (CRO), 13 lutein cysts (LCs), and 9 non-classifiable cysts (NCCs). In addition to the histological classification, results were interpreted according to subject medical history, clinical examination outcome, and macroscopic observations during ovariohysterectomy. Dogs with ovarian cysts (OCs) and associated reproductive perturbations were mostly nulliparous, of large breed, and had an average of $9.5{\pm}3$ years. Prolonged or shortened inter-estrus intervals of past heats, however, seemed to be relatively low-risk factors for the development of OCs in dogs. Furthermore, we provide histological observations of a rarely seen canine LC including a degenerated oocyte in the central cavity.

• 센서학회지
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• 제29권1호
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• pp.19-26
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• 2020

Electrocardiogram (ECG) classification has become an essential task of modern day wearable devices, and can be used to detect cardiovascular diseases. State-of-the-art Artificial Intelligence (AI)-based ECG classifiers have been designed using various artificial neural networks (ANNs). Despite their high accuracy, ANNs require significant computational resources and power. Herein, three different ANNs have been compared: multilayer perceptron (MLP), convolutional neural network (CNN), and spiking neural network (SNN) only for the ECG classification. The ANN model has been developed in Python and Theano, trained on a central processing unit (CPU) platform, and deployed on a PYNQ-Z2 FPGA board to validate the model using a Jupyter notebook. Meanwhile, the hardware accelerator is designed with Overlay, which is a hardware library on PYNQ. For classification, the MIT-BIH dataset obtained from the Physionet library is used. The resulting ANN system can accurately classify four ECG types: normal, atrial premature contraction, left bundle branch block, and premature ventricular contraction. The performance of the ECG classifier models is evaluated based on accuracy and power. Among the three AI algorithms, the SNN requires the lowest power consumption of 0.226 W on-chip, followed by MLP (1.677 W), and CNN (2.266 W). However, the highest accuracy is achieved by the CNN (95%), followed by MLP (76%) and SNN (90%).

• 센서학회지
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• 제30권1호
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• pp.20-24
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• 2021

The electrocardiogram (ECG) is one of the most extensively employed signals used to diagnose and predict cardiovascular diseases (CVDs). In recent years, several deep learning (DL) models have been proposed to improve detection accuracy. Among these, deep neural networks (DNNs) are the most popular, wherein the features are extracted automatically. Despite the increment in classification accuracy, DL models require exorbitant computational resources and power. This causes the mapping of DNNs to be slow; in addition, the mapping is challenging for a wearable device. Embedded systems have constrained power and memory resources. Therefore full-precision DNNs are not easily deployable on devices. To make the neural network faster and more power-efficient, spiking neural networks (SNNs) have been introduced for fewer operations and less complex hardware resources. However, the conventional SNN has low accuracy and high computational cost. Therefore, this paper proposes a new binarized SNN which modifies the synaptic weights of SNN constraining it to be binary (+1 and -1). In the simulation results, this paper compares the DL models and SNNs and evaluates which model is optimal for ECG classification. Although there is a slight compromise in accuracy, the latter proves to be energy-efficient.

• IMMUNE NETWORK
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• 제21권3호
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• pp.21.1-21.22
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• 2021

Myeloid-derived suppressor cells (MDSCs) have strong immunosuppressive activity and are morphologically similar to conventional monocytes and granulocytes. The development and classification of these cells have, however, been controversial. The activation network of MDSCs is relatively complex, and their mechanism of action is poorly understood, creating an avenue for further research. In recent years, MDSCs have been found to play an important role in immune regulation and in effectively inhibiting the activity of effector lymphocytes. Under certain conditions, particularly in the case of tissue damage or inflammation, MDSCs play a leading role in the immune response of the central nervous system. In cancer, however, this can lead to tumor immune evasion and the development of related diseases. Under cancerous conditions, tumors often alter bone marrow formation, thus affecting progenitor cell differentiation, and ultimately, MDSC accumulation. MDSCs are important contributors to tumor progression and play a key role in promoting tumor growth and metastasis, and even reduce the efficacy of immunotherapy. Currently, a number of studies have demonstrated that MDSCs play a key regulatory role in many clinical diseases. In light of these studies, this review discusses the origin of MDSCs, the mechanisms underlying their activation, their role in a variety of clinical diseases, and their function in immune response regulation.

• Tuberculosis and Respiratory Diseases
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• 제83권3호
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• pp.195-200
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• 2020

The disease concept of interstitial lung disease with idiopathic pulmonary fibrosis at its core has been relied on for many years depending on morphological classification. The separation of non-specific interstitial pneumonia with a relatively good prognosis from usual interstitial pneumonia is also based on the perception that morphology enables predict the prognosis. Beginning with dust-exposed lungs, initially, interstitial pneumonia is classified by anatomical pathology. Diagnostic imaging has dramatically improved the diagnostic technology for surviving patients through the introduction of high-resolution computed tomography scan. And now, with the introduction of therapeutics, the direction of diagnosis is turning. It can be broadly classified into to make known the importance of early diagnosis, and to understand the importance of predicting the speed of progression/deterioration of pathological conditions. For this reason, the insight of "early lesions" has been discussed. There are reports that the presence or absence of interstitial lung abnormalities affects the prognosis. Searching for a biomarker is another prognostic indicator search. However, as is the case with many chronic diseases, pathological conditions that progress linearly are extremely rare. Rather, it progresses while changing in response to environmental factors. In interstitial lung disease, deterioration of respiratory functions most closely reflect prognosis. Treatment is determined by combining dynamic indicators as faithful indicators of restrictive impairments. Reconsidering the history being classified under the disease concept, the need to reorganize treatment targets based on common pathological phenotype is under discussed. What is the disease concept? That aspect changes with the discussion of improving prognosis.

• Tuberculosis and Respiratory Diseases
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• 제38권2호
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• pp.108-115
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• 1991

Endobronchial tuberculosis is a serious disease which is frequently complicated with bronchial stenosis, and it may simulate a bronchial asthma or bronchogenic carcinoma. We have analyzed the clinical characteristics of endobronchial tuberculosis in 166 patients, and we introduce new classification of endobronchial tuberculosis. Endobronchial tuberculosis is classified into seven subtypes as stenotic type with fibrosis, stenotic type without fibrosis, actively caseating type, tumorous type, ulcerative type, granular type and nonspecific bronchitic type, according to the bronchoscopic findings. Actively caseaing type, stenotic type without fibrosis, nonspecific bronchitic type and stenotic type with fibrosis are predominant in the order of frequency, but ulcerative type and granular type are relatively rare. Stenotic type with or without fibrosis, actively caseating type and tumorous type of endobronchial tuberculosis are closely related to bronchial stenoses. We believe that our new classification of endobronchial tuberculosis, which is based on bronchoscopic features, is helpful to understand the pathogenesis of disease and to make a therapeutic plan for preventing or minimizing bronchial stenosis.