Che 1-kwŏn. Kodae-kŭndae sasang -- che 2-kwŏn. Hyŏndae sasang.

1. Wŏnjŏn Chosŏn Yuhaksa -- 2. Chosŏn Yuhaksa -- 3. Chosŏn sasangsa -- 4. Sasang pʻyŏn -- 5. Munhak pʻyŏn.

Artificial intelligence techniques in general and convolutional neural networks in particular have attained successful results in medical image analysis and classification. A deep CNN architecture has been proposed in this paper for the diagnosis of COVID-19 based on the chest X-ray image classification. Due to the nonavailability of sufficient-size and good-quality chest X-ray image dataset, an effective and accurate CNN classification was a challenge. To deal with these complexities such as the availability of a very-small-sized and imbalanced dataset with image-quality (...) issues, the dataset has been preprocessed in different phases using different techniques to achieve an effective training dataset for the proposed CNN model to attain its best performance. The preprocessing stages of the datasets performed in this study include dataset balancing, medical experts’ image analysis, and data augmentation. The experimental results have shown the overall accuracy as high as 99.5% which demonstrates the good capability of the proposed CNN model in the current application domain. The CNN model has been tested in two scenarios. In the first scenario, the model has been tested using the 100 X-ray images of the original processed dataset which achieved an accuracy of 100%. In the second scenario, the model has been tested using an independent dataset of COVID-19 X-ray images. The performance in this test scenario was as high as 99.5%. To further prove that the proposed model outperforms other models, a comparative analysis has been done with some of the machine learning algorithms. The proposed model has outperformed all the models generally and specifically when the model testing was done using an independent testing set. (shrink)

BackgroundAlthough the Life-Sustaining Treatment (LST) Decision Act was enforced in 2018 in Korea, data on whether it is well established in actual clinical settings are limited. Hospital-acquired pneumonia (HAP) is a common nosocomial infection with high mortality. However, there are limited data on the end-of-life (EOL) decision of patients with HAP. Therefore, we aimed to examine clinical characteristics and outcomes according to the EOL decision for patients with HAP.MethodsThis multicenter study enrolled patients with HAP at 16 referral hospitals retrospectively from (...) January to December 2019. EOL decisions included do-not-resuscitate (DNR), withholding of LST, and withdrawal of LST. Descriptive and Kaplan–Meier curve analyses for survival were performed.ResultsOf 1,131 patients with HAP, 283 deceased patients with EOL decisions (105 cases of DNR, 108 cases of withholding of LST, and 70 cases of withdrawal of LST) were analyzed. The median age was 74 (IQR 63–81) years. The prevalence of solid malignant tumors was high (32.4% vs. 46.3% vs. 54.3%, P = 0.011), and the ICU admission rate was lower (42.9% vs. 35.2% vs. 24.3%, P = 0.042) in the withdrawal group. The prevalence of multidrug-resistant pathogens, impaired consciousness, and cough was significantly lower in the withdrawal group. Kaplan–Meier curve analysis revealed that 30-day and 60-day survival rates were higher in the withdrawal group than in the DNR and withholding groups (log-rank P = 0.021 and 0.018). The survival of the withdrawal group was markedly decreased after 40 days; thus, the withdrawal decision was made around this time. Among patients aged below 80 years, the rates of EOL decisions were not different (P = 0.430); however, mong patients aged over 80 years, the rate of withdrawal was significantly lower than that of DNR and withholding (P = 0.001).ConclusionsAfter the LST Decision Act was enforced in Korea, a DNR order was still common in EOL decisions. Baseline characteristics and outcomes were similar between the DNR and withholding groups; however, differences were observed in the withdrawal group. Withdrawal decisions seemed to be made at the late stage of dying. Therefore, advance care planning for patients with HAP is needed. (shrink)

Background Participants' understanding of clinical trials is important in informed consent. However, little is known about what information participants really want to know. Aims To demonstrate the existence of a discrepancy between participants' understanding and their desire to know. Methods The participants in clinical trials at Seoul National University Hospital were surveyed. The survey consisted of 11 statements based on the essential elements of informed consent. The participants gave two responses to each statement on a five-point Likert scale to rate (...) their subjective understanding and desire to know, respectively. Information discrepancy was defined as the difference between these two ratings: if understanding exceeded desire to know for a particular item, it was defined as ‘over-informed’; if desire to know exceeded understanding for a particular item, it was defined as ‘under-informed’. Results Participants reported good understanding of ‘voluntariness’, ‘duration’, ‘study involves research’ and poor understanding of ‘confidentiality’, ‘compensation’, ‘benefits’, ‘procedures’ and ‘risks or discomforts’. For ‘risks or discomforts’, ‘who to contact’, ‘voluntariness’, ‘duration’ and ‘procedures’, participants reported high desire to know compared with ‘confidentiality’, ‘purpose’, ‘study involves research’ and ‘benefits’. The elements ‘study involves research’, ‘voluntariness’, ‘duration’, ‘purpose’ and ‘who to contact’ were over-informed, while ‘compensation’, ‘risks or discomforts’, ‘procedures’, ‘confidentiality’ and ‘benefits’ were under-informed. Participants over 50 years of age, those without a college education and those whose participation was less voluntary were relatively less informed about the clinical trials. Conclusions An information discrepancy was observed between the participants' understanding and their desire to know. By putting more emphasis on under-informed elements, the quality of informed consent could be improved. (shrink)

As documented by Darwin 150 years ago, emotion expressed in human faces readily draws our attention and promotes sympathetic emotional reactions. How do such reactions to the expression of emotion affect our goal-directed actions? Despite the substantial advance made in the neural mechanisms of both cognitive control and emotional processing, it is not yet known well how these two systems interact. Here, we studied how emotion expressed in human faces influences cognitive control of conflict processing, spatial selective attention and inhibitory (...) control in particular, using the Eriksen flanker paradigm. In this task, participants viewed displays of a central target face flanked by peripheral faces and were asked to judge the gender of the target face; task-irrelevant emotion expressions were embedded in the target face, the flanking faces, or both. We also monitored how emotion expression affects gender judgment performance while varying the relative timing between the target and flanker faces. As previously reported, we found robust gender congruency effects, namely slower responses to the target faces whose gender was incongruent with that of the flanker faces, when the flankers preceded the target by 0.1 s. When the flankers further advanced the target by 0.3 s, however, the congruency effect vanished in most of the viewing conditions, except for when emotion was expressed only in the flanking faces or when congruent emotion was expressed in the target and flanking faces. These results suggest that emotional saliency can prolong a substantial degree of conflict by diverting bottom-up attention away from the target, and that inhibitory control on task-irrelevant information from flanking stimuli is deterred by the emotional congruency between target and flanking stimuli. (shrink)

The present study develops an artificial agent that plays the iterative chicken game based on a computational model that describes human behavior in competitive social interactions in terms of fairness. The computational model we adopted in this study, named as the self-concept fairness model, decides the agent’s action according to the evaluation of fairness of both opponent and self. We implemented the artificial agent in a computer program with a set of parameters adjustable by researchers. These parameters allow researchers to (...) determine the extent to which the agent behaves aggressively or cooperatively. To demonstrate the use of the proposed method for the investigation of human behavior, we performed an experiment in which human participants played the iterative chicken game against the artificial agent. Participants were divided into two groups, each being informed to play with either a person or the computer. The behavioral analysis results showed that the proposed method can induce changes in the behavioral pattern of human players by changing the agent’s behavioral pattern. Also, we found that participants tended to be more sensitive to fairness when they played with a human opponent than with a computer opponent. These results support that the artificial agent developed in this study will be useful to investigate human behavior in competitive social interactions. (shrink)

Modern schooling in Korea, which was officially established by law in 1949, is well known for its function as an engine of economic success in modern Korea. Although this fact seems to be world-wid...

어떤 만남은 운명이다! 조선시대 전방위 지식인 다산 정약용, 그의 가르침을 따라 평생을 산 단 한 사람, 황상 "부지런하고 부지런하고 부지런하라" "학생은 있지만 제자는 없다"는 탄식의 소리가 높아지고 있다. 존경과 사랑이라는 단어가 무색하게 진정한 스승도 진정한 제자도 드문 요즈음이다. 정민 교수에 의해 200년 전 다산 정약용과 그의 제자 황상 사이에 이어진 도탑고 신실한 사제 간의 정리가 울림이 커다란 의미로 되살아난다.