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최은성,류혜정,채병윤,Choi, Eun-Sung,Ryu, Hye-Jeong,Chae, Byung-Yoon 대한한방안이비인후피부과학회 1996 한방안이비인후피부과학회지 Vol.9 No.1
We observed 79 patients, who visited the Department of Oph. & Otorhinolaryngology in Oriental medicine of Kyung Hee University Medical Center from July 1995 to June. 1996, with the complaint of decreased visual acuity. The results were as follows. 1. In the incidence of decreased visual acuity, men's was $46.84\%$(37 cases) and women's was $53.16\%$(42 cases), which showed that more women were suffering decreased visual acuity than men. In the incidence of myopic ametropia and astigmatic ametropia among the total patients, men's was $44.62\%$(29 cases) and $37.50\%$(9 cases) each, and women's was $55.38\%$(36 cases) and $62.50\%$( 15 cases) each, which also showed that more women were suffering myopia and astigmatism than men. 2. The average age of patients was 11.08 years at the first visit. The most were the patients from 6 to 15 years old, with 63 cases($79.74\%$). 3. The age of onset in the decreased visual acuity was mainly 6∼10 years with 45 cases($56.96\%$). In the case of myopic ametropia and astigmatic ametropia, the age of onset was also mainly 6∼10 years with 65 cases($60.00\%$), and with 12 cases($50.00\%$) each. 4. In ABO blood type, the frequency was, A type, O type, B type and AB type in order. In men, O type was the most, while in women, A type. 5. In the liking for cool or warm food or tepidity, the liking for cool food was the most in both men and women. 6. The type of decreased visual acuity was mainly myopic ametropia with 65 cases($82.28\%$). Astigmatic ametropia was $30.38\%$ with 24 cases, hyperopic ametropia $2.53\%$ with 4 cases, and the decreased visual acuity accompanied by amblyopia $7.59\%$ with 4 cases. 7. At the first visit, the average visual acuity of O.D. was 0.29 and that of O.S.. 0.24, which showed that O.S.. is worse than O.D.. The visual acuity below 0.2 was the most, $63.29\%\;in\;O.D..\;72.15\%$ in O.S.. 8. In the treatment period, 4∼7 weeks occupied $35.44\%$ with 28 cases, 8∼11 weeks $30.38\%$ with 24 cases, so the treatment period was mainly these two periods with 52 cases($65.82\%$). 9. The average frequency of acupuncture treatment per week was mainly 2.1∼3.0 times with 45 cases($56.96\%$). In this case, men was 24 cases($53.33\%$) and women 21 cases($46.67\%$), so men was more than women. 10. The frequency of herbal prescription was mainly Gamijungjitang and Gamijingjibogansan with 76 cases($85.39\%$).
경기지역 20∼30대 여성의 골 건강 관련 영양지식 수준과 칼슘 섭취 관련 식행동 및 영양교육과의 연관성
최은성 ( Eun-sung Choi ),박찬윤 ( Chan Yoon Park ) 대한영양사협회 2023 대한영양사협회 학술지 Vol.29 No.1
Osteoporosis is a major health problem confronting middle-aged women today. Enhancing calcium intake in early adulthood can increase the rate of calcium gain in bone. In this study, we investigated the association of bone health-related nutritional knowledge levels with calcium-related dietary behavior and nutrition education among women. Data were collected using questionnaires from 347 women aged 20∼30 residing in Gyeonggi-do. Subjects were categorized into two groups according to their bone health-related nutritional knowledge (high or low-knowledge group). Knowledge related to bone health and calcium, and dietary habits was assessed, and the preference for and intake frequency of calcium-rich food were collected and analyzed using food frequency questionnaires. The high-knowledge group showed a significantly higher rate of nutritional education experience (33.9%) when compared with the low-knowledge group (18.9%). Not only were the perceptions regarding milk and dairy products more positive in the high-knowledge group (P<0.05), but the intake frequency of calcium-rich foods, such as tofu, soybean, and anchovies, was also higher in this group compared to the low-knowledge group (P<0.05). Overall, the preference for all calcium-rich foods was positively correlated to their intake frequency (P<0.05). Nutrition education experience and the recognition of the need for such education were positively correlated with the bone health-related nutrition knowledge score (P<0.05). In conclusion, bone health-related nutritional knowledge can affect calcium-related dietary behavior and increase the intake of calcium-rich food of 20∼30-year-old women and this can contribute to the prevention of osteoporosis. To improve bone health-related nutritional knowledge among young women, it may be important to provide nutrition education.
증례 : 감염 ; 황열 백신 접종 후 발생한 간염 1예
최은성 ( Eun Sung Choi ),배귀현 ( Kwi Hyun Bae ),정영의 ( Young Eui Jeong ),주영란 ( Young Ran Ju ),김현아 ( Hyun Ah Kim ),류성열 ( Seong Yeol Ryu ) 대한내과학회 2011 대한내과학회지 Vol.80 No.2S
23세 남자 환자가 황열 백신 접종 7일 후 고열, 근육통, 오심 주소로 내원하여 anti-YFV Ig M 양성 소견으로 황열 백신 접종 후 발생한 내장향성 질환(고열과 간염)으로 진단받고 입원 24일 후 증상 호전보여 퇴원하였다. 황열(yellow fever)은 세계 여러 지역에서 계속해서 발생하여 유병률과 사망률이 높은 질환으로 주로 아프리카나 중남미의 열대우림 지역에서 유행하며 10-20%에서 신부전, 간부전, 현저한 서맥을 동반한 고열이 나타나는 전형적인 황열 증상을 나타낸다. 예방을 위해서는 황열 백신의 접종이 가장 중요하며, 부작용은 비교적 적은 것으로 알려져 있으나 드물지만 중증의 합병증이 외국문헌에는 보고되고 있으나 아직까지 국내에는 YEL-AND 1예 외 보고된 바는 없다. 이에 저자는 국내에서 처음으로 황열 백신 접종 후 내장향성 질환(고열과 간염)이 발생한 1예를 경험하였기에 문헌고찰과 함께 보고하는 바이다. This report describes a case of yellow fever vaccine-associated viscerotropic disease (YEL-AVD) that occurred after vaccination in a 23-year-old male. Seven days after vaccination, our patient presented with fever, myalgia, and nausea. The IgM enzyme-linked immunosorbent assay (ELISA) for yellow fever virus was positive. After a 24 day hospitalization, he recovered and was discharged. Yellow fever is a viral hemorrhagic febrile illness caused by a flavivirus and transmitted by mosquitoes. The clinical presentation ranges from a mild febrile illness to a serious infection, leading to hepatic and renal failure, myocardial injury, hemorrhage, and shock, with a case fatality rate of 20-30%. Because yellow fever is a potentially fatal disease, vaccination is encouraged for people traveling to high-risk areas. Although considered a safe vaccine, severe adverse reactions have been reported. In 2001, rare, but severe, acute viscerotropic disease following vaccination was first described. We report the case of a 23-year-old male with fever and hepatitis following vaccination with 17D yellow fever vaccine. (Korean J Med 2011;80:S301-S304)
기계학습을 이용한 리튬 이온 배터리 고체 전해질의 기계적 물성 예측
최은성(EunSeong Choi),조준호(Joon ho Jo),민경민(Kyoungmin Min) 대한기계학회 2020 대한기계학회 춘추학술대회 Vol.2020 No.12
Li-ion batteries have great output, high energy density and a long battery life, so they are being studied and commercialized. However, in the case of Li SSEs(Solid-State Electrolytes), performance is severely limited due to interfacial contact stability problems and the formation and growth of dendrite. In order to analyze and solve this problem, it is necessary to knowing bulk and shear modulus of that compound. But The number of Li SSEs calculated mechanical properties is not enough. Predicting mechanical properties with Machine Learning techniques is much more efficient than experiments and DFT(Density-functional theory) calculations. So we used machine learning regression algorithm with Materials project database screened. As a result, mechanical properties of candidates were obtained with reasonable high accuracy. This makes it possible to search for a wide range of candidates materials in an economical way to select the ideal one.
이선경(Sunkyung Lee),최은성(Eunseong Choi),정선호(Seonho Jeong),이종욱(Jongwuk Lee) 한국정보과학회 2021 정보과학회논문지 Vol.48 No.12
기계 독해(Machine Reading Comprehension)란 컴퓨터가 주어진 텍스트의 의미를 이해 및 이를 평가하는 방법으로, 자연어 이해를 위한 중요한 기술 중 하나이다. 주어진 글에 대해서 질의가 주어졌을 때, 이에 대한 올바른 응답을 찾는 질의-응답이 가장 대표적인 기계 독해 과제이다. 기계 독해 기술은 최근 심층 인공신경망 기반의 자연어 처리 기술의 발달에 따라 획기적인 성능 개선을 보였다. 그럼에도 불구하고, 주어진 데이터가 희소할 때 성능 개선에 어려움이 있을 수 있다. 이를 해결하기 위해 본 논문에서는 단어 단위 및 문장 단위의 텍스트 편집을 통한 데이터 증강 기법을 활용하여 기존 모델의 변경을 최소화하며 성능 개선을 하고자 한다. 즉, 본 연구에서는 영어 질의응답 데이터에서 가장 널리 활용되고 있는 사전 학습된 언어 모델 기반의 기계 독해 모델에 데이터 증강 기법을 적용하여 기존 모델 대비성능이 향상되는 것을 확인하였다. Machine reading comprehension is a method of understanding the meaning and performing inference over a given text by computers, and it is one of the most essential techniques for understanding natural language. The question answering task yields a way to test the reasoning ability of intelligent systems. Nowadays, machine reading comprehension techniques performance has significantly improved following the recent progress of deep neural networks. Nevertheless, there may be challenges in improving performance when data is sparse. To address this issue, we leverage word-level and sentence-level data augmentation techniques through text editing, while minimizing changes to the existing models and cost. In this work, we propose data augmentation methods for a pre-trained language model, which is most widely used in English question answering tasks, to confirm the improved performance over the existing models.