• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.33-34
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• 2020

사용자의 피부 관리 및 피부질환을 검사하는 기존의 어플리케이션은 유도 질문에 따른 사용자의 응답을 기반으로 결과를 유추하기 때문에 부정확한 진단 결과를 야기한다. 본 논문에서는 사용자의 미용관련 피부질환 이미지를 바탕으로 딥러닝 이미지 인식 기술 적용하여 건선, 사마귀, 여드름, 한포진을 대상으로 피부 미용질환에 대한 식별 정보를 제공하는 어플리케이션을 제시한다. 또한 이미지 인식률이 높은 ResNet과 SE-ResNet 알고리즘을 적용하여 피부질환 식별 적용 시 효과성을 실험적으로 비교한다.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.555-560
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• 2021

Recently, as people's interest in facial skin beauty has increased, research on skin disease recognition for facial skin beauty is being conducted by using deep learning. These studies recognized a variety of skin diseases, including acne. Existing studies can recognize only the single skin diseases, but skin diseases that occur on the face can enact in a more diverse and complex manner. Therefore, in this paper, complex skin diseases such as acne, blackheads, freckles, age spots, normal skin, and whiteheads are identified using the Inception-ResNet V2 deep learning mode with multi-label classification. The accuracy was 98.8%, hamming loss was 0.003, and precision, recall, F1-Score achieved 96.6% or more for each single class.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.25-34
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• 2020

In this paper, we empirically compare the effectiveness of training models to recognize beauty-related skin disease using supervised deep learning algorithms. Recently, deep learning algorithms are being actively applied for various fields such as industry, education, and medical. For instance, in the medical field, the ability to diagnose cutaneous cancer using deep learning based artificial intelligence has improved to the experts level. However, there are still insufficient cases applied to disease related to skin beauty. This study experimentally compares the effectiveness of identifying beauty-related skin disease by applying deep learning algorithms, considering CNN, ResNet, and SE-ResNet. The experimental results using these training models show that the accuracy of CNN is 71.5% on average, ResNet is 90.6% on average, and SE-ResNet is 95.3% on average. In particular, the SE-ResNet-50 model, which is a SE-ResNet algorithm with 50 hierarchical structures, showed the most effective result for identifying beauty-related skin diseases with an average accuracy of 96.2%. The purpose of this paper is to study effective training and methods of deep learning algorithms in consideration of the identification for beauty-related skin disease. Thus, it will be able to contribute to the development of services used to treat and easy the skin disease.

• Journal of the Korea Convergence Society
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• v.10 no.6
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• pp.287-297
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• 2019

The purpose of this study was to examine the relationship of body-shape perception and periodontal diseases in female adolescents based on the sixth 3rd-year(2015) data of the National Health and Nutrition Examination Survey. The subjects in this study were 211 female teenagers who were at the western ages of 12 to 18. As a result of analyzing, it's found that the body-shape perception of the female teens were linked to age, sleep hours, BMI, weight control and toothbrushing frequency, and whether they had periodontal diseases or not was found to be under the influence of age, smoking, sleep hours, stress, BMI and toothbrushing frequency. When the relationship between their body-shape perception and peridontal diseases was analyzed by controlling the confounders, the adolescents who considered their own bodies to be obese suffered from 3.18-fold more periodontal diseases(OR=3.18, 95% CI: 1.21, 8.38) than the teenagers who considered their body shape to be average. In the future, oral health care should be provided in consideration of the mental health of female adolescents to prevent periodontal diseases.

• Journal of the Korean Orthopaedic Association
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• v.54 no.2
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• pp.192-196
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• 2019

Iatrogenic calcinosis cutis is due to the intravenous administration of calcium gluconate or calcium chloride to treat hypocalcemia. The arthors report three cases of calcinosis cutis with calcifications involving the upper or lower extremities in neonates following the extravasation of calcium gluconate. Three neonates, a 2-week-old girl, 4-week-old boy, and a 4-week-old girl, were consulted for indurated nodules after the intravenous administration of calcium gluconate at the intensive care unit. Complete remission of palpable nodule and calcification was observed on the radiograph at three weeks, four weeks and six months after the initial presentation in each. All three neonates with iatrogenic calcinosis curtis were resolved spontaneously without functional and cosmetic complications. According to enhancement of the patient's cognition about benign disease, a suitable explanation of the disease and avoiding unnecessary treatment through an early diagnosis of iatrogenic calcinosis cutis will reduce a number of potential medical malpractice disputes.