• Journal of Gastric Cancer
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• v.7 no.2
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• pp.67-73
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• 2007

Purpose: There have been several comparative studies that have focused on elderly groups of patients with gastric cancer. However, new criteria are needed for this elderly group because of the longer life span of Korean people. The diagnosis of gastric cancer has sometimes been missed in the young age group. The perioperative risk is high in the elderly age group because of their combined diseases. This study was designed to determine the differences of the clinicopathologic features and the prognosis between young and elderly patients with gastric cancer. Materials and Methods: Eighty patients were divided in two groups and these patients were selected for making comparison between young and elderly groups of patients with gastric cancer. The young age group consisted of 31 patients who were aged 35 years old or less. The elderly age group was made up of 49 patients who were aged 75 years old or above. Results: For the clinicopathologic features, the young age group was characterized by a high incidence of the poorly differentiated type of adenocarcinoma and the diffuse type too, according to the Lauren classification. On the other hand, the elderly group was characterized by a high incidence of poorly to moderate differentiated adenocarcinoma and also the intestinal type according to the Lauren classification. The other clinical differences were unremarkable. Additionally, there was no survival advantage in the young age group compared to the elderly group. Conclusion: There were no clinicopathologic and prognostic differences between both extreme age groups. So, active surgical treatment is recommended even for the elderly patients group.

• Journal of Sasang Constitutional Medicine
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• v.8 no.2
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• pp.41-68
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• 1996

This thesis is a try for examining the historical characteristics of Constiutional medicine. For this purpose, I have examined their theory, and made a comparison carefully. Through this study, I have obtained several results as following. Both Chang and Lee lived in the time of change, which was unstable and uncertain. Under the condition, they both rejected following the existing trends of learned circles, and developed new thoughts and clinical techniques. They rejected superstitious beliefs and fatalism, and conducted the pursuit of experimental knowledge and rationale idea. Clinical experience was the very base of their study. They both criticized the bad habits of abuse of tonifing medication and health seeking. Especially Lee regarded control of emotion and regulation of a way of life as the best way for preservation of one's health. Chang regarded pathogenic factors as the ultimate factor of diseases, and strived for eliminating pathogenic factors, but L brought to a conclusion that the final factor of diseases was what is called "heart" itself, and emotional changes were the most essential causes of disease. It can be said that the pathogenesis insisted by Chang can be called The insistence that pathologic factors are the very etiology of all the disease (邪氣致病論), or all the diseases result from pathologic factors. And his whole remedy can be summarized as following, A study on the method of eliminating pathogenic factors. But the purpose of Constitutional medicine is to correct imbalance intrinsic to one's internal organs. In this aspect, Constitutional medicine is a "regulatory medicine". Depending on the classification of six vital substances, Chang classified all disease into six categories. These were based on symptoms and sings represented. While classification of diseases made by Lee was likely to rely upon constitutional characteristics. Chang thought that the three remedies made up of perspiration, purgation, vomiting were the most efficient way of eliminating pathogenic factors. Lee, however, thought those weren't methods of eliminating pathogenic factors but the best ways restoring one's self-regulation power. Chang thought that all the febrile disease essentially has a tendency in properties to belong to "heat", but Lee pointed out that pathologic processes are variable in accordance with constitutional features. They both regarded pathogenesis of diabetes as fire. That is to say, fire is the most essential factor of diabetes. And there are many risk factors such as inappropriate foods, drugs, climate, etc., but Lee thought what is most important is heart. Putting all accounts together, medical characteristics of Chang are similar to those of T aiyinjen and Shaoyangjen, and have no relation to those of those of Shaoyinjen. Therefore we can conclude that Chang understood pathologic processes of disease of T aiyinjen and Shaoyangjen, whether he knew about constitutional features or not.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.2
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• pp.207-216
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• 2024

As big data was built due to the 4th Industrial Revolution, personalized services increased rapidly. As a result, the amount of personal information collected from online services has increased, and concerns about users' personal information leakage and privacy infringement have increased. Online service providers provide privacy policies to address concerns about privacy infringement of users, but privacy policies are often misused due to the long and complex problem that it is difficult for users to directly identify risk items. Therefore, there is a need for a method that can automatically check whether the privacy policy is safe. However, the safety verification technique of the conventional blacklist and machine learning-based privacy policy has a problem that is difficult to expand or has low accessibility. In this paper, to solve the problem, we propose a safety verification technique for the privacy policy using the GPT-3.5 API, which is a generative artificial intelligence. Classification work can be performed evenin a new environment, and it shows the possibility that the general public without expertise can easily inspect the privacy policy. In the experiment, how accurately the blacklist-based privacy policy and the GPT-based privacy policy classify safe and unsafe sentences and the time spent on classification was measured. According to the experimental results, the proposed technique showed 10.34% higher accuracy on average than the conventional blacklist-based sentence safety verification technique.

• Journal of Society of Preventive Korean Medicine
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• v.23 no.2
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• pp.117-127
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• 2019

Objectives : Korean medicine practice is not specifically described in medical law, and then has always been a quarrel. So far The criteria for judgment in Korean Medicine Doctor's Medical Devices Using should clinically prove it only by Korean medicine theory and academic Traditionally descending from old ancestors. Comprehensively review of Korean Medicine Doctor's Medical Devices Using and Duty of Care, and then present a new understandings to determine future Korean Medicine Practice. Method : An existing court cases of Korean Medicine Doctor's Medical Devices Using and Duty of Care were reviewed. After reviewing various papers published for several years, various opinions were reviewed and suggested. Results : The range of Korean Medicine Doctor's Medical Devices Using has changed since the 1951 National Medical Law stipulated Korean medicine as medical professionals. The issue of the recent ruling that distinguishes medical practice from Korean medicine practice were condensed into what emphasis to interpret amongst 1) The basic principles of learning, 2) Curriculum and professionalism, 3) Risks. The Constitutional Court's ruling was important in order of 'Risk', 'curriculum and expertise', and 'basic principles of learning.' A duty of Care means an obligation to pay attention to something. A duty of Care does not mean a "highest level," but requires a "best care" and does "best under given conditions." Even in the duty of Care, Because Korean medicine has a purpose to protect and promote the health of the people, Some standards of western medicine have to be adapted to the current general medical technology. Korean Medicine doctors can recognize the duty of care in the "some basic range" of knowledge belonging to western medicine. Conclusions : The interpretation of Korean Medicine practice are currently in compatible the argument that should clearly divide Korean medicine from Western medicine, and that should be changed in light of the changing medical environment. Therefore If Korean medicine's standard is applied to the extent to which Korean Medicine doctors are educated, it is necessary to define a new definition to actively interpret Korean Medical practice. The academic basis of Korean medicine and the level of Korean medicine practice based on the books that are traditionally available, and then current textbooks of Korean Medicine College, Korean Medicine Clinical Care Guidelines, and classification of Korean standard medical practices should be standardized. Increasingly, Korean Medicine practice should be interpreted according to reality, focusing on protecting and promoting the health of the people rather than academic differences.

• The Journal of the Korea Contents Association
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• v.18 no.8
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• pp.525-535
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• 2018

If the frequency of a particular class is excessively higher than the frequency of other classes in the classification problem, data imbalance problems occur, which make machine learning distorted. Corporate bankruptcy prediction often suffers from data imbalance problems since the ratio of insolvent companies is generally very low, whereas the ratio of solvent companies is very high. To mitigate these problems, it is required to apply a proper sampling technique. Until now, oversampling techniques which adjust the class distribution of a data set by sampling minor class with replacement have popularly been used. However, they are a risk of overfitting. Under this background, this study proposes ROSE(Random Over Sampling Examples) technique which is proposed by Menardi and Torelli in 2014 for the effective corporate bankruptcy prediction. The ROSE technique creates new learning samples by synthesizing the samples for learning, so it leads to better prediction accuracy of the classifiers while avoiding the risk of overfitting. Specifically, our study proposes to combine the ROSE method with SVM(support vector machine), which is known as the best binary classifier. We applied the proposed method to a real-world bankruptcy prediction case of a Korean major bank, and compared its performance with other sampling techniques. Experimental results showed that ROSE contributed to the improvement of the prediction accuracy of SVM in bankruptcy prediction compared to other techniques, with statistical significance. These results shed a light on the fact that ROSE can be a good alternative for resolving data imbalance problems of the prediction problems in social science area other than bankruptcy prediction.

• Journal of Korea Water Resources Association
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• v.56 no.4
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• pp.261-272
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• 2023

In recent years, natural disasters such as heavy rainfall and typhoons have occurred more frequently, and their severity has increased due to climate change. The Korea Meteorological Administration (KMA) currently uses the same criteria for all regions in Korea for watch and warning based on the maximum cumulative rainfall with durations of 3-hour and 12-hour to reduce damage. However, KMA's criteria do not consider the regional characteristics of damages caused by heavy rainfall and typhoon events. In this regard, it is necessary to develop new criteria considering regional characteristics of damage and cumulative rainfalls in durations, establishing four stages: blue, yellow, orange, and red. A classification model, called DSCM (Disaster Severity Classification Model), for the four-stage disaster severity was developed using four machine learning models (Decision Tree, Support Vector Machine, Random Forest, and XGBoost). This study applied DSCM to local governments of Seoul, Incheon, and Gyeonggi Province province. To develop DSCM, we used data on rainfall, cumulative rainfall, maximum rainfalls for durations of 3-hour and 12-hour, and antecedent rainfall as independent variables, and a 4-class damage scale for heavy rain damage and typhoon damage for each local government as dependent variables. As a result, the Decision Tree model had the highest accuracy with an F1-Score of 0.56. We believe that this developed DSCM can help identify disaster risk at each stage and contribute to reducing damage through efficient disaster management for local governments based on specific events.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4517-4520
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• 2012

Introduction: Northeastern Iran is known as a high risk area of upper gastrointestinal cancers. Recent reports have suggested a declining trend for these cancers as well as an increase in the incidence of other malignancies including breast cancer. Our present aim was to describe the epidemiological pattern of breast cancer in this region during 2004-2009. Methods: All new cancer cases from public and private diagnostic and therapeutic centers of Golestan province were registered. A structured questionnaire was prepared and used based on the standerds of the International Association of Cancer Registries. The international classification of diseases for oncology was considered for coding. Age standardized incidence rates (ASR) of breast cancer were calculated. Results: A total of 11,038 new cancer cases were registered during 2004-2009, of which, 1,101 (10%) were females with breast cancer. The median age of the breast cancer patients was 46 years. The ASR for breast cancer was 28 per 100,000 person-years. We found an unusual rapid increase in breast cancer rate at the age of 25 years. The ASR of breast cancer was significantly lower in females from Turkmen ethnicity and those from rural areas(P value <0.01). Conclusion: Our study showed high rate of breast cancer in Golestan province of Iran. We found an unusual peak of breast cancer in young women. So, the age of starting screening programs may need to be revised in this area. The rate of breast cancer was significantly lower in women from Turkmen ethnicity. Further studies are warranted to clarify the role of important determinants, especially regarding the ethnic disparity, on breast cancer in this region.

• Journal of the Korean Institute of Gas
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• v.22 no.4
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• pp.27-31
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• 2018

Classification of explosion hazard areas is very important in terms of cost and safety in the workplace handling flammable materials. This is because the radius of the hazardous area determines whether or not the explosion-proof equipment is installed in the electrical machinery and apparatus. From November 6, 2017, KS C IEC-60079-10-1: 2015 will be issued and applied as a new standard. It is important to understand and apply the difference between the existing standard and the new standard. Leakage coefficients and compression factors were added to the leakage calculation formula, and the formula of evaporation pool leakage, application of leakage ball size, and shape of explosion hazard area were applied. The range of the safety factor K has also been changed. Also, in the radius of the hazardous area, the existing standard applies the number of ventilation to the virtual volume, but the revised standard is calculated by using the leakage characteristic value. In this study, we investigated the differences from existing standards in terms of ventilation and dilution and examined the effect on the radius of the hazard area. Comparisons and analyzes were carried out by applying revised standards to workplaces where existing explosion hazard locations were selected. The results showed that even if the ventilation and dilution were successful, the risk radius was not substantially affected.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.722-729
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• 2010

Prediction problems are widely used in medical domains. For example, computer aided diagnosis or prognosis is a key component in a CDSS (Clinical Decision Support System). SVMs with nonlinear kernels like RBF kernels, have shown superior accuracy in prediction problems. However, they are not preferred by physicians for medical prediction problems because nonlinear SVMs are difficult to visualize, thus it is hard to provide intuitive interpretation of prediction results to physicians. Nomogram was proposed to visualize SVM classification models. However, it cannot visualize nonlinear SVM models. Localized Radial Basis Function (LRBF) was proposed which shows comparable accuracy as the RBF kernel while the LRBF kernel is easier to interpret since it can be linearly decomposed. This paper presents a new tool named VRIFA, which integrates the nomogram and LRBF kernel to provide users with an interactive visualization of nonlinear SVM models, VRIFA visualizes the internal structure of nonlinear SVM models showing the effect of each feature, the magnitude of the effect, and the change at the prediction output. VRIFA also performs nomogram-based feature selection while training a model in order to remove noise or redundant features and improve the prediction accuracy. The area under the ROC curve (AUC) can be used to evaluate the prediction result when the data set is highly imbalanced. The tool can be used by biomedical researchers for computer-aided diagnosis and risk factor analysis for diseases.

• 한국노년학
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• v.40 no.2
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• pp.325-340
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• 2020

Early diagnosis and intervention of dementia is critical to minimize future risk and cost for patients and their families. The purpose of this study was to develop and validate Figure-Copy Test(FCT), as a new dementia screening test, that can measure neurological damage and cognitive impairment, and then to examine whether the grading precesses for screening can be automated through machine learning procedure by using FCT imag es. For this end, FCT, Korean version of MMSE for Dementia Screening (MMSE-DS) and Clock Drawing Test were administrated to a total of 270 participants from normal and damaged elderly groups. Results demonstrated that FCT scores showed high internal constancy and significant correlation coefficients with the other two test scores. Discriminant analyses showed that the accuracy of classification for the normal and damag ed g roups using FCT were 90.8% and 77.1%, respectively, and these were relatively higher than the other two tests. Importantly, we identified that the participants whose MMSE-DS scores were higher than the cutoff but showed lower scores in FCT were successfully screened out through clinical diagnosis. Finally, machine learning using the FCT image data showed an accuracy of 73.70%. In conclusion, our results suggest that FCT, a newly developed drawing test, can be easily implemented for efficient dementia screening.