• Journal of Nutrition and Health
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• v.51 no.6
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• pp.556-566
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• 2018

Purpose: This study was designed to determine the relationship between health behaviors and high levels of low-density lipoprotein-cholesterol (LDL-cholesterol) according to cardiovascular risk factors among Korean adults. Methods: This cross-sectional study was based on the sixth Korea national health and nutrition examination survey (KNHANES VI). Participants were 13,841 adults aged 19 years and older. Cardiovascular risk factors were stroke, myocardial infarction or angina, diabetes mellitus, smoking, hypertension, aging, high density lipoprotein-cholesterol (HDL-cholesterol) under 40 mg/dL and HDL-cholesterol over 60 mg/dL. Cardiovascular risk groups were classified as very high risk (stroke, myocardial infarction or angina), high risk (diabetes mellitus), moderate risk (over 2 risk factors), and low risk (below 1 risk factor). The prevalence of high LDL-cholesterol was calculated using the LDL-cholesterol target level according to cardiovascular risk group. Results: The prevalence of high LDL-cholesterol was 25.5% in males and 21.7% in females. Complex sample cross tabulation demonstrated that the high LDL-cholesterol and normal groups differed significantly according to age, education, body mass index, percentage of energy from carbohydrate, fat, saturated fat and n-6 in males and females. These two groups were also significantly different according to smoking in males and the percentage of energy from n-3 in females. Complex sample multiple logistic regression analysis adjusted for multiple confounding factors demonstrated that the probability of high LDL-cholesterol was significantly associated with current smoking (OR: 1.66, 95% CI: 1.40-1.99), obesity (OR: 1.95, 95% CI: 1.64-2.31) in males, and current smoking (OR: 1.73, 95% CI: 1.19-2.52), obesity (OR: 1.63, 95% CI: 1.39-1.90), percentage of energy from n-3 (quartile 1 vs. quartile 2; OR: 0.77, 95% CI: 0.62-0.96; quartile 1 vs. quartile 3; OR: 0.73, 95% CI: 0.56-0.94; quartile 1 vs. quartile 4: OR: 0.67, 95% CI: 0.51-0.87) in females. Conclusion: This study reveals the impact of smoking, obesity, energy percentage of nutrient intake on LDL-cholesterol.

• Journal of the Korean Society of Radiology
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• v.13 no.3
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• pp.359-369
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• 2019

To evaluate the effect of simultaneous use of platelet glycoprotein IIb / IIIa receptor blocker and catheter assisted thrombus aspiration in the treatment of coronary stent thrombosis. 267 patients ($64.6{\pm}12.1years$, 187 men) with stent thrombosis on coronary angiography at Chonnam National University Hospital from July 2008 to July 2017 were enrolled. We devided two groups based on treatment modalities: Group I (N=32, platelet glycoprotein IIb / IIIa receptor blocker and thrombo-aspiration), Group II (N =235, either platelet glycoprotein IIb /IIIa receptor blocker or thrombo-aspiration, or none of both), and the major cardiac events including death, revascularization and stent thrombosis were followed up for 1 year. There were no significant differences in clinical characteristics between the two groups including age (Group I: $60.8{\pm}12.9$ vs. Group II: $65.1{\pm}11.9$, p= 0.603), male (Group I: 75.0% vs. Group II: 69.4%, p=0.681), and left ventricular ejection fraction (Group I: $58.1{\pm}9.0%$ vs. Group II: $59.5{\pm}11.9%$, p= 0.127). The major cardiac events did not differ between the two groups (Group I: 12.5% vs. Group II: 23.8%, p=0.180). The secondary endopoints were as followings: The mortality rate (Group I: 0% vs. 13.2%, Group II: p=0.034), target lesion revascularization (Group I: 9.4% vs Group II: 6.4%, p=0.461) and stent thrombosis (Group I: 3.1% vs. Group II: 4.7%, p=1.000). In conclusion, in the treatment of coronary artery stent thrombosis, simultaneous use of platelet glycoprotein IIb / IIIa receptor blocker and thrombus aspiration was associated with better clinical outcomes regarding 1 year mortality.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.4
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• pp.41-54
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• 2021

This study targets the urban park corresponding to the core areas (Hubs) of Green Infrastructure and estimates their value utilizing the Contingent Valuation Method (CVM) and determines the planning factors which affect them. The research aims to provide basic data for supporting the value improvement in the planning stage for urban parks representing green infrastructure. The primary purpose of this research is to derive variables that affect economic value and planning factors to improve the use-value of urban parks, one of the Hubs of the green infrastructure. In this study, Sejong Lake Park, located in Sejong City, is the target site. This study collected the responses of 105 people by conducting a survey on the intention to pay for the use-value and the planning factors that affect it, targeting visitors to Sejong Lake Park. The study conducts Contingent Valuation Method (CVM) on this survey responses. The results are as follows: first, as a result of analyzing the variables which affect willingness to pay for use-value, residence and age influence the willingness to pay significantly among socioeconomic characteristics. Next, the survey responses of Double-bounded dichotomous choices (DB-DC) CVM are converted into variables through statistic techniques. Furthermore, the variables are used for a Logit model to draw coefficients. The average willingness to pay per person for the use-value of Sejong Lake Park using the derived coefficients was approximately found to be 8,597 won. Therefore, as of 2019, Sejong Lake Park, with a total of 430,000 visitors, is estimated to have an annual economic value of 3.7 billion won. Third, the average Likert scale of the planning factor affecting the decision to pay for the economic value of Sejong Lake Park was the highest along the waterfront landscape, and the convenience facilities and waterfront landscape showed the highest willingness to pay, 10,000 won. In the range between 2,500 won and 5,000 won, the waterfront area ranks highest. Therefore, it can be said that visitors to Sejong Lake Park take account of the economic value of using the waterfront landscape the most. This study is meaningful as a thesis on use-value and the planning factors that affected value evaluation results of urban parks, and the analysis of the correlation between the planning factors of urban parks as hubs located in urban areas.

• Korean Journal of Psychosomatic Medicine
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• v.31 no.2
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• pp.165-172
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• 2023

Objectives : The purpose of this study is to determine whether there is a significant difference in the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio according to the history of suicide attempt in patients with psychiatric diseases. Methods : A medical record review was conducted on patients who had been hospitalized in Konyang University Hospital since 2021-03-01 to 2023-02-28 to collect demographic and clinical characteristics. T-test for continuous variables and Chi-square test for categorical variables were performed to determine demographic differences according to the history of suicide attempt, and the ANCOVA test was performed to compare the average value of peripheral inflammatory marker according to the history of suicide attempt with gender and age as covariates. One-way variance analysis was performed to determine whether the number of suicide attempt causes significant difference of the peripheral inflammatory marker. Results : The final analysis target of this study was 266 patients, 101 had history of suicide attempt, and 165 had no history of suicide attempt. The neutrophil-to-lymphocyte ratio (p<0.001) and platelet-to-lymphocyte ratio (p<0.001) were higher in patients with the history of suicide attempt than patients without the history of suicide attempt, but the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio were not significantly increased depending on the serial increase of number of suicide attempts. Conclusions : This study suggests that peripheral inflammatory markers are meaningful and easily accessible indicators for predicting the risk of suicide attempt in psychiatric patients. We expect that prospective follow-up study will be conducted with more subjects and controlled potential confounding variables.

• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

• Journal of Distribution Research
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• v.15 no.4
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• pp.1-19
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• 2010

As having the movement of developing private brand (PB) goods, domestic big retailers are facing up with new problems. Thus, it is required studies of PB products, and how consumers recognize PB products as a consideration commodity set. Also, it is worthy in order that it gives us the important meaning on the marketing strategy with focusing on evaluating the differences between customers buying PB grocery goods with respect to demographic characteristics and purchasing behaviors. PB has some advantages for customers and retailers. However, according to AC Nielson's report (2005), Asian and emerging market has 1/5 sales relatively to Western countries. But we can assume that the emerging market has the most potential growth through this result. As a result from several other studies, it becomes necessary to not only increase the rate of selling composition of PB product temporarily, but also analyze the characteristics of customers using big retailers and segmenting customer groups to make PB product as a consideration commodity set for them. In addition, it is needed to have a variety of acts of marketing. From studies related to PB, there is a prejudice - cheap products have low quality - but, evaluation by customers who have used those products shows neutral stand, and there is a study representing that it is the most important to accumulate the belief between the retailers selling PB products and consumers using those for the accurate evaluation and intention on purchasing. Also, by the result from analyzing the characteristics of customers buying PB products, we could assume that higher income and higher education level, more preference on PB products. Especially, according to TNS's research, the primary targets of PB product are 30's who seeks value for money and planned spending habits, and 40's who have teenager children, and are interested in encouraging themselves. This paper used Probit model to analyze the characteristics of consumers. This model helps us to analyze with the variables representing the demographic characteristics of consumers (gender, age, educational level, occupation, income level, living area), and variables related to purchasing behavior (visiting frequency on big retailers, the average amount that they pay for goods in there, and check-up which brand made those goods). The method we used in this study is by man to man interview and survey on-line with the rate of 89% and 11% in Seoul and Gyunggi Province, respectively, for about one month from the beginning of February, 2008. As a result of this, under the assumption that people buy PB products more as long as they go shopping more, it was not meaningful for target groups which we pointed out as frequently visiting customers to be. Although, we have expected women buy more PB products than men do, gender doesn't mean anything for the result. And, it has inferred that married people buy more PB goods than singles do. It was also meaningless with variables related to occupation. Because housewives are often exposed to any kind of supermarket than workers are, we could not get any relatives. Moreover, we couldn't proof that younger generation prefer big retailers more than older people who 50~60's. Education levels doesn't affect on the purchase of PB product as well. Related to living area, the result is statistically not similar as we expected whether living in Seoul or not. It shows there is no relationship with the preference on retail brands and PB products, and it is similar with the study researched by TNS(2008) that customers tend to buy PB product impulsively no matter which brand it is and where they are even though their shopping place is the big market where customers are often using. Variables on which we had meaningful results are income level and living place. That is, customers who have 3,000,000~6,000,000 WON every month on average are more willing to buy PB products than other customers whose income is over 6,000,000 WON, and residents not living in Seoul prefer PB goods than those who are living in Seoul. To explain more about what we got, if there is only one condition about customer's visiting frequency on big retails, we could come up with this result that more exposed to PB products, more purchasing frequency. Consequently, it brings the important insight that large retailers have to prepare something to make customers visit them often to increase selling rate of PB products. To demonstrate the result of analyzing more, what is more efficient variables are demographically including marital status, income level, and residential area to buy items that affect the PB products and could include the frequency of visiting large markets by the purchase habits. Specifically, then, married couples rather than singles, middle-income customers than high-income customers, and local residents not living in Seoul than customers in Seoul are more likely to purchase PB goods. In addition, as long as a customer visits two times more, then the purchasing rate of PB products is to increase over 5.3%. Therefore, it seems that retailers are better to make a shopping place as fun and comfortable places. With overwhelming the idea that PB products are just cheap, one-time purchase goods, it is needed to increase the loyalty on those goods like NB products, try to make PB products as a consideration products set, and occur to sustainable sales. Especially, as suggested by this paper, it seems like it strongly needs to identify the characteristics of customers who prefer PB, to segment those customers, and to select the main target, and to do positioning with well-planned marketing strategies. Then, it is able to give us a meaningful point on marketing strategy by developing the field of PB study, identifying the difference of life style and shopping habits of customers.

• Journal of radiological science and technology
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• v.31 no.1
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• pp.17-23
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• 2008

Purpose : Because there is a difference depending on the environment as for an inspection equipment the important part of bone density scan and the precision/accuracy of a tester, the management of quality must be made systematically. The equipment failure caused by overload effect due to the aged equipment and the increase of a patient was made frequently. Thus, the replacement of equipment and additional purchases of new bonedensity equipment caused a compatibility problem in tracking patients. This study wants to know whether the clinical changes of patient's bonedensity can be accurately and precisely reflected when used it compatiblly like the existing equipment after equipment replacement and expansion. Materials and methods : Two equipments of GE Lunar Prodigy Advance(P1 and P2) and the Phantom HOLOGIC Spine Road(HSP) were used to measure equipment precision. Each device scans 20 times so that precision data was acquired from the phantom(Group 1). The precision of a tester was measured by shooting twice the same patient, every 15 members from each of the target equipment in 120 women(average age 48.78, 20-60 years old)(Group 2). In addition, the measurement of the precision of a tester and the cross-calibration data were made by scanning 20 times in each of the equipment using HSP, based on the data obtained from the management of quality using phantom(ASP) every morning (Group 3). The same patient was shot only once in one equipment alternately to make the measurement of the precision of a tester and the cross-calibration data in 120 women(average age 48.78, 20-60 years old)(Group 4). Results : It is steady equipment according to daily Q.C Data with $0.996\;g/cm^2$, change value(%CV) 0.08. The mean${\pm}$SD and a %CV price are ALP in Group 1(P1 : $1.064{\pm}0.002\;g/cm^2$, $%CV=0.190\;g/cm^2$, P2 : $1.061{\pm}0.003\;g/cm^2$, %CV=0.192). The mean${\pm}$SD and a %CV price are P1 : $1.187{\pm}0.002\;g/cm^2$, $%CV=0.164\;g/cm^2$, P2 : $1.198{\pm}0.002\;g/cm^2$, %CV=0.163 in Group 2. The average error${\pm}$2SD and %CV are P1 - (spine: $0.001{\pm}0.03\;g/cm^2$, %CV=0.94, Femur: $0.001{\pm}0.019\;g/cm^2$, %CV=0.96), P2 - (spine: $0.002{\pm}0.018\;g/cm^2$, %CV=0.55, Femur: $0.001{\pm}0.013\;g/cm^2$, %CV=0.48) in Group 3. The average error${\pm}2SD$, %CV, and r value was spine : $0.006{\pm}0.024\;g/cm^2$, %CV=0.86, r=0.995, Femur: $0{\pm}0.014\;g/cm^2$, %CV=0.54, r=0.998 in Group 4. Conclusion: Both LUNAR ASP CV% and HOLOGIC Spine Phantom are included in the normal range of error of ${\pm}2%$ defined in ISCD. BMD measurement keeps a relatively constant value, so showing excellent repeatability. The Phantom has homogeneous characteristics, but it has limitations to reflect the clinical part including variations in patient's body weight or body fat. As a result, it is believed that quality control using Phantom will be useful to check mis-calibration of the equipment used. A value measured a patient two times with one equipment, and that of double-crossed two equipment are all included within 2SD Value in the Bland - Altman Graph compared results of Group 3 with Group 4. The r value of 0.99 or higher in Linear regression analysis(Regression Analysis) indicated high precision and correlation. Therefore, it revealed that two compatible equipment did not affect in tracking the patients. Regular testing equipment and capabilities of a tester, then appropriate calibration will have to be achieved in order to calculate confidential BMD.

• Journal of Global Scholars of Marketing Science
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• v.19 no.4
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• pp.44-56
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• 2009

Impulse purchasing is defined as an immediate purchase with no pre-shopping intentions. Previous studies of impulse buying have focused primarily on factors linked to marketing mix variables, situational factors, and consumer demographics and traits. In previous studies, marketing mix variables such as product category, product type, and atmospheric factors including advertising, coupons, sales events, promotional stimuli at the point of sale, and media format have been used to evaluate product information. Some authors have also focused on situational factors surrounding the consumer. Factors such as the availability of credit card usage, time available, transportability of the products, and the presence and number of shopping companions were found to have a positive impact on impulse buying and/or impulse tendency. Research has also been conducted to evaluate the effects of individual characteristics such as the age, gender, and educational level of the consumer, as well as perceived crowding, stimulation, and the need for touch, on impulse purchasing. In summary, previous studies have found that all products can be purchased impulsively (Vohs and Faber, 2007), that situational factors affect and/or at least facilitate impulse purchasing behavior, and that various individual traits are closely linked to impulse buying. The recent introduction of new distribution channels such as home shopping channels, discount stores, and Internet stores that are open 24 hours a day increases the probability of impulse purchasing. However, previous literature has focused predominantly on situational and marketing variables and thus studies that consider critical consumer characteristics are still lacking. To fill this gap in the literature, the present study builds on this third tradition of research and focuses on individual trait variables, which have rarely been studied. More specifically, the current study investigates whether impulse buying tendency has a positive impact on impulse buying behavior, and evaluates how consumer characteristics such as the need for cognitive closure (NFCC), psychological wellbeing, and susceptibility to interpersonal influences affect the tendency of consumers towards impulse buying. The survey results reveal that while consumer affective impulsivity has a strong positive impact on impulse buying behavior, cognitive impulsivity has no impact on impulse buying behavior. Furthermore, affective impulse buying tendency is driven by sub-components of NFCC such as decisiveness and discomfort with ambiguity, psychological wellbeing constructs such as environmental control and purpose in life, and by normative and informational influences. In addition, cognitive impulse tendency is driven by sub-components of NFCC such as decisiveness, discomfort with ambiguity, and close-mindedness, and the psychological wellbeing constructs of environmental control, as well as normative and informational influences. The present study has significant theoretical implications. First, affective impulsivity has a strong impact on impulse purchase behavior. Previous studies based on affectivity and flow theories proposed that low to moderate levels of impulsivity are driven by reduced self-control or a failure of self-regulatory mechanisms. The present study confirms the above proposition. Second, the present study also contributes to the literature by confirming that impulse buying tendency can be viewed as a two-dimensional concept with both affective and cognitive dimensions, and illustrates that impulse purchase behavior is explained mainly by affective impulsivity, not by cognitive impulsivity. Third, the current study accommodates new constructs such as psychological wellbeing and NFCC as potential influencing factors in the research model, thereby contributing to the existing literature. Fourth, by incorporating multi-dimensional concepts such as psychological wellbeing and NFCC, more diverse aspects of consumer information processing can be evaluated. Fifth, the current study also extends the existing literature by confirming the two competing routes of normative and informational influences. Normative influence occurs when individuals conform to the expectations of others or to enhance his/her self-image. Whereas informational influence occurs when individuals search for information from knowledgeable others or making inferences based upon observations of the behavior of others. The present study shows that these two competing routes of social influence can be attributed to different sources of influence power. The current study also has many practical implications. First, it suggests that people with affective impulsivity may be primary targets to whom companies should pay closer attention. Cultivating a more amenable and mood-elevating shopping environment will appeal to this segment. Second, the present results demonstrate that NFCC is closely related to the cognitive dimension of impulsivity. These people are driven by careless thoughts, not by feelings or excitement. Rational advertising at the point of purchase will attract these customers. Third, people susceptible to normative influences are another potential target market. Retailers and manufacturers could appeal to this segment by advertising their products and/or services as products that can be used to identify with or conform to the expectations of others in the aspiration group. However, retailers should avoid targeting people susceptible to informational influences as a segment market. These people are engaged in an extensive information search relevant to their purchase, and therefore more elaborate, long-term rational advertising messages, which can be internalized into these consumers' thought processes, will appeal to this segment. The current findings should be interpreted with caution for several reasons. The study used a small convenience sample, and only investigated behavior in two dimensions. Accordingly, future studies should incorporate a sample with more diverse characteristics and measure different aspects of behavior. Future studies should also investigate personality traits closely related to affectivity theories. Trait variables such as sensory curiosity, interpersonal curiosity, and atmospheric responsiveness are interesting areas for future investigation.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.95-108
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• 2017

Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.

• Tuberculosis and Respiratory Diseases
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• v.45 no.1
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• pp.5-19
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• 1998

Introduction: Direct histologic and bacteriologic examination of a representative specimen of lung tissue is the only certain method of providing an accurate diagnosis in various pulmonary diseases including diffuse pulmonary diseases. The purpose of national survey was to define the indication, incidence, effectiveness, safety and complication of open and thoracoscopic lung biopsy in korea. Methods: A multicenter registry of 37 university or general hospitals equipped more than 400 patient's bed were retrospectively collected and analyzed for 3 years from the January 1994 to December 1996 using the same registry protocol. Results: 1) There were 511 cases from the 37 hospitals during 3 years. The mean age was 50.2 years(${\pm}15.1$ years) and men was more prevalent than women(54.9% vs 45.9%). 2) The open lung biopsy was performed in 313 cases(62%) and thoracoscopic lung biopsy was performed in 192 cases(38%). The incidence of lung biopsy was more higher in diffuse lung disease(305 cases, 59.7%) than in localized lung disease(206 cases, 40.3%) 3) The duration after abnormalities was found in chest X-ray until lung biopsy was 82.4 days(open lung biopsy: 72.8 days, thoracoscopic lung biopsy: 99.4 days). The bronchoscopy was performed in 272 cases(53.2%), bronchoalveolar lavage was performed in 123 cases(24.1%) and percutaneous lung biopsy was performed in 72 cases(14.1%) before open or thoracoscopic lung biopsy. 4) There were 230 cases(45.0%) of interstitial lung disease, 133 cases(26.0%) of thoracic malignancies, 118 cases(23.1%) of infectious lung disease including tuberculosis and 30 cases (5.9 %) of other lung diseases including congenital anomalies. No significant differences were noted in diagnostic rate and disease characteristics between open lung biopsy and thoracoscopic lung biopsy. 5) The final diagnosis through an open or thoracoscopic lung biopsy was as same as the presumptive diagnosis before the biopsy in 302 cases(59.2%). The identical diagnostic rate was 66.5% in interstitial lung diseases, 58.7% in thoracic malignancies, 32.7% in lung infections, 55.1 % in pulmonary tuberculosis, 62.5% in other lung diseases including congenital anomalies. 6) One days after lung biopsy, $PaCO_2$ was increased from the prebiopsy level of $38.9{\pm}5.8mmHg$ to the $40.2{\pm}7.1mmHg$(P<0.05) and $PaO_2/FiO_2$ was decreased from the prebiopsy level of $380.3{\pm}109.3mmHg$ to the $339.2{\pm}138.2mmHg$(P=0.01). 7) There was a 10.1 % of complication after lung biopsy. The complication rate in open lung biopsy was much higher than in thoracoscopic lung biopsy(12.4% vs 5.8%, P<0.05). The incidence of complication was pneumothorax(23 cases, 4.6%), hemothorax(7 cases, 1.4%), death(6 cases, 1.2%) and others(15 cases, 2.9%). 8) The 5 cases of death due to lung biopsy were associated with open lung biopsy and one fatal case did not describe the method of lung biopsy. The underlying disease was 3 cases of thoracic malignancies(2 cases of bronchoalveolar cell cancer and one malignant mesothelioma), 2 cases of metastatic lung cancer, and one interstitial lung disease. The duration between open lung biopsy and death was $15.5{\pm}9.9$ days. 9) Despite the lung biopsy, 19 cases (3.7%) could not diagnosed. These findings were caused by biopsy was taken other than target lesion(5 cases), too small size to interpretate(3 cases), pathologic inability(11 cases). 10) The contribution of open or thoracoscopic lung biopsy to the final diagnosis was defininitely helpful(334 cases, 66.5%), moderately helpful(140 cases, 27.9%), not helpful or impossible to judge(28 cases, 5.6%). Overall, open or thoracoscopic lung biopsy were helpful to diagnose the lung lesion in 94.4 % of total cases. Conclusions: The open or thoracoscopic lung biopsy were relatively safe and reliable diagnostic method of lung lesion which could not diagnosed by other diagnostic approaches such as bronchoscopy. We recommend the thoracoscopic lung biopsy when the patients were in critical condition because the thoracoscopic biopsy was more safe and have equal diagnostic results compared with the open lung biopsy.