• Journal of Preventive Medicine and Public Health
• /
• v.48 no.2
• /
• pp.105-110
• /
• 2015

Objectives: Recently, low systolic blood pressure (SBP) was found to be associated with an increased risk of death from vascular diseases in a rural elderly population in Korea. However, evidence on the association between low SBP and vascular diseases is scarce. The aim of this study was to prospectively examine the association between low SBP and mortality from all causes and vascular diseases in older middle-aged Korean men. Methods: From 2004 to 2010, 94 085 Korean Vietnam War veterans were followed-up for deaths. The adjusted hazard ratios (aHR) were calculated using the Cox proportional hazard model. A stratified analysis was conducted by age at enrollment. SBP was self-reported by a postal survey in 2004. Results: Among the participants aged 60 and older, the lowest SBP (<90 mmHg) category had an elevated aHR for mortality from all causes (aHR, 1.9; 95% confidence interval [CI], 1.2 to 3.1) and vascular diseases (International Classification of Disease, 10th revision, I00-I99; aHR, 3.2; 95% CI, 1.2 to 8.4) compared to those with an SBP of 100 to 119 mmHg. Those with an SBP below 80 mmHg (aHR, 4.5; 95% CI, 1.1 to 18.8) and those with an SBP of 80 to 89 mmHg (aHR, 3.1; 95% CI, 0.9 to 10.2) also had an increased risk of vascular mortality, compared to those with an SBP of 90 to 119 mmHg. This association was sustained when excluding the first two years of follow-up or preexisting vascular diseases. In men younger than 60 years, the association of low SBP was weaker than that in those aged 60 years or older. Conclusions: Our findings suggest that low SBP (<90 mmHg) may increase vascular mortality in Korean men aged 60 years or older.

• Journal of Sasang Constitutional Medicine
• /
• v.23 no.3
• /
• pp.361-373
• /
• 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.

• Journal of the Korean Society of Radiology
• /
• v.15 no.4
• /
• pp.455-461
• /
• 2021

Cardiomegaly is one of the most common diseases seen on chest X-rays, but if it is not detected early, it can cause serious complications. In view of this, in recent years, many researches on image analysis in which deep learning algorithms using artificial intelligence are applied to medical care have been conducted with the development of various science and technology fields. In this paper, we would like to evaluate whether the Inception V3 deep learning model is a useful model for the classification of Cardiomegaly using chest X-ray images. For the images used, a total of 1026 chest X-ray images of patients diagnosed with normal heart and those diagnosed with Cardiomegaly in Kyungpook National University Hospital were used. As a result of the experiment, the classification accuracy and loss of the Inception V3 deep learning model according to the presence or absence of Cardiomegaly were 96.0% and 0.22%, respectively. From the research results, it was found that the Inception V3 deep learning model is an excellent deep learning model for feature extraction and classification of chest image data. The Inception V3 deep learning model is considered to be a useful deep learning model for classification of chest diseases, and if such excellent research results are obtained by conducting research using a little more variety of medical image data, I think it will be great help for doctor's diagnosis in future.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.23 no.3
• /
• pp.287-298
• /
• 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.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.6
• /
• pp.786-792
• /
• 2012

A microarray is a collection of thousands of DNAs or RNAs arranged on a substrate, and it enables one to navigate large amounts of gene expression. However, a researcher uses his designed experimental methods to focus on particular phenotypes from the available mass of data. In this paper, we used MicroRNAs(miRNAs) and Protein-Protein Interation(PPI) databases to enhance and expand meanings in microarray data. Further, the expanded data are linked with the Online Mendelian Inheritance in Man(OMIM), and International Statistical Classification of Diseases and Related Health Problems, $10^{th}$ Revision(ICD-10), in order to extract common genetic relationships between diseases. This approach, we expect, should provide new biological views.

• Journal of Veterinary Science
• /
• v.19 no.6
• /
• pp.725-734
• /
• 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.

• Journal of Sensor Science and Technology
• /
• v.29 no.1
• /
• pp.19-26
• /
• 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%).

• Journal of Sensor Science and Technology
• /
• v.30 no.1
• /
• pp.20-24
• /
• 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
• /
• v.21 no.3
• /
• pp.21.1-21.22
• /
• 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
• /
• v.83 no.3
• /
• pp.195-200
• /
• 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.