• 한국컴퓨터정보학회논문지
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• 제27권3호
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• pp.137-147
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• 2022

피부상태의 진단과 관리는 뷰티산업종사자와 화장품산업종사자에게 그 역할을 수행함에 있어서 매우 기초적이며 중요한 기능이다. 정확한 피부상태 진단과 관리를 위해서는 고객의 피부상태와 요구사항을 잘 파악하는 것이 필요하다. 본 논문에서는 피부상태 진단 및 관리를 위해 소셜미디어의 빅데이터를 사용하여 피부상태 진단 및 관리를 지원하는 빅데이터기반 피부관리정보시스템 SCIS를 개발하였다. 개발된 시스템을 사용하여 텍스트 정보 중심의 피부상태 진단과 관리를 위한 핵심 정보를 분석하고 추출할 수 있다. 본 논문에서 개발된 피부관리정보시스템 SCIS는 빅데이터 수집단계, 텍스트전처리단계, 이미지전처리단계, 텍스트단어분석단계로 구성되어 있다. SCIS는 피부진단 및 관리에 필요한 빅데이터를 수집하고, 텍스트 정보를 대상으로 핵심단어의 단순빈도분석, 상대빈도분석, 동시출현분석, 상관성분석을 통해 핵심단어 및 주제를 추출하였다. 또한 추출된 핵심단어 및 정보를 분석하고 산포도, NetworkX, t-SNE 및 클러스터링 등의 다양한 시각화 처리를 함으로써 피부상태 진단 및 관리에 있어 이를 효율적으로 사용할 수 있도록 하였다.

• 한국컴퓨터정보학회논문지
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• 제27권8호
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• pp.241-251
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• 2022

화장품 및 뷰티산업에서 고객의 피부상태 진단과 관리는 중요한 필수기능이다. 소셜미디어 환경이 사회 전 분야에 확산되고 일반화되면서 피부 상태의 진단과 관리에 대한 다양하고 섬세한 고민과 요구 사항의 질문과 답변의 상호작용이 소셜미디어 커뮤니티에서 활발하게 다루어지고 있다. 그러나 소셜미디어 정보는 매우 다양하고 비정형적인 방대한 빅데이터이므로 적절한 피부상태 정보분석과 인공지능 기술을 접목한 지능화된 피부상태 진단 시스템이 필요하다. 본 논문에서는 소셜미디어의 텍스트 분석정보를 학습데이터로 가공하여 고객의 피부상태를 지능적으로 진단 및 관리하기 위한 피부상태진단시스템 SCDIS를 개발하였다. SCDIS에서는 딥러닝 기계학습 방법인 인공신경망 기술을 사용하여 자동적으로 피부상태 유형을 진단하는 인공신경망 모델 AnnTFIDF을 빌드업하여 사용하였다. 인공신경망 모델 AnnTFIDF의 성능은 테스트샘플 데이터를 사용하여 분석되었으며, 피부상태 유형 진단 예측 값의 정확성은 약 95%의 높은 성능을 나타내었다. 본 논문의 실험 및 성능분석결과를 통하여 SCDIS는 화장품 및 뷰티산업 분야의 피부상태 분석 및 진단 관리 과정에서 효율적으로 사용 가능한 지능화된 도구로 평가할 수 있다. 본 논문에서 제안된 시스템은 소셜미디어 기반의 새로운 환경에서 화장품 및 피부미용에 대한 사용자의 요구를 체계적으로 파악하고 진단하는 기초 기술로 사용 가능할 것이다. 그리고 이 연구는 새로운 기술 트렌드인 맞춤형 화장품제조와 소비자중심의 뷰티산업기술 수요를 해결하기 위한 기초 연구로 사용될 수 있을 것이다.

• 디지털산업정보학회논문지
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• 제14권4호
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• pp.69-77
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• 2018

The malignant melanoma accounts for about 1 to 3% of the total malignant tumor in the West, especially in the US, it is a disease that causes more than 9,000 deaths each year. Generally, skin lesions are difficult to detect the features through photography. In this paper, we propose a computer-aided diagnosis algorithm based on deep learning for classification of malignant melanoma and benign skin tumor in RGB channel skin images. The proposed deep learning model configures the tumor lesion segmentation model and a classification model of malignant melanoma. First, U-Net was used to segment a skin lesion area in the dermoscopic image. We could implement algorithms to classify malignant melanoma and benign tumor using skin lesion image and results of expert's labeling in ResNet. The U-Net model obtained a dice similarity coefficient of 83.45% compared with results of expert's labeling. The classification accuracy of malignant melanoma obtained the 83.06%. As the result, it is expected that the proposed artificial intelligence algorithm will utilize as a computer-aided diagnosis algorithm and help to detect malignant melanoma at an early stage.

• Asian Pacific Journal of Cancer Prevention
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• 제16권8호
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• pp.3403-3406
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• 2015

Background: Skin biopsy is the method to assist clinicians to make definite dermatological diagnosis which further helps in holistic management. Skin cancers are relatively rare clinical diagnosis in developing countries like Nepal, but the prevalence is on rise. Objectives: To investigate the profile of skin biopsies and frequencies and pattern of skin cancers in a tertiary care centre of Western Nepal. Materials and Methods: The materials consisted of 434 biopsies (1.37%) out of 31,450 OPD visits performed in the Department of Dermatology, Manipal Teaching Hospital, Pokhara, Nepal, during the period of Dec 2011-Nov 2014. Data were collected and analyzed using SPSS-16 with reference to incidence, age, sex, race and clinical and histopathological features. Results: The commonest disorders observed in biopsies were papulosquamous lesions, skin tuberculosis of different types, benign skin tumors, leprosy, collagen and fungal diseases. Viral diseases were rarely seen, probably due to straight forward clinical diagnosis. Dermatological malignancies accounted for 55/434 (12.67%) of biopsies. Skin disorders in general were commoner in females 280/434 (64%), including malignancies 32/55(58.2%). Mean age of patients with skin cancer was 54.5 years. Facilities for proper laboratory investigation of dermatological disorders will improve the quality of life. Conclusions: The most prevalent lesion in skin biopsies was papulosquamous disorders followed by skin tuberculosis of different types. Dermatological malignancy constituted 55/434 (12.67%) cases. The prevalence of skin malignancy is on rise in Nepalese society probably due to increase in life expectancy and better diagnostic services.

• 가정∙방문간호학회지
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• 제5권
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• pp.47-60
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• 1998

This study was done to identify basic information in classifying nursing diagnoses and nursing interventions needed for the further development of computerized nursing care plans. Data were collected by reviewing charts of 123 home care clients who had active disease, for whom at least one nursing diagnosis was on the chart, and who had been discharged. Data included demographics, medical orders, nursing diagnoses and nursing interventions. The results of the study, which found the most frequent medical diagnoses to be cancer (40.7%) and brain injury (26.8%), showed that 'Impaired Skin Integrity'(18.3%), 'Risk for Infection'(15.0%), 'Altered Nutrition, Less than Body Requirements'(13.8%), and 'Risk for Impaired Skin Integ rity'(9.9%) were the most frequent nursing diagnoses. 'Pressure Ulcer Care'(28.4%) was the most frequent intervention for 'Impaired Skin Integrity', 'Infection Protection'(16.0%) for 'Risk of Infection', 'Nutrition Counseling'(26.8%) for 'Altered Nutrition' and 'Positioning'(22.0%) for 'Risk for Skin Integrity Impairment', Comparison of interventions with the Nursing Intervention Classification(NIC) showed that the most frequent interventions were in the domain 'Basic Physiological' (33.94%), followed by 'Behavioral'(27.8%), and 'Complex Physiological' (22.6%). Interventions related to teaching family to give care at home could not be classified in the NIC scheme. Examination of the frequency of NIC interventions showed that for the domain 'Activity & Exercise Management', 75% of the interventions were used, but for seven domains, none were used. For the domain 'Immobility Management', 93% of the times that an intervention was used, it was 'Positioning', for the domain 'Tissue Perfusion Management', 'IV Therapy' (59.1%) and for the domain 'Elimination Management', 'Tube Care: Urinary'(54.0%). The nursing diagnoses 'Altered Urinary Elimination' and 'Im paired Physical Mobility' were both used with these clients, but neither 'Fluid Volume Deficit' nor 'Risk of Fluid Volume Deficit' were used rather 'IV Therapy' was an intervention for 'Altered Nutrition, Less than Body Requirements', A comparison of clients with cancer and those with brain injury showed that interventions for the nursing diagnosis 'Impaired Skin Integrity' were more frequent for the clients with cancer, interventions for 'Risk of Infection' were similar for the two groups but for clients with cancer there were more interventions for' Altered Nutrition'. Examination of the nursing diagnoses leading to the intervention 'Positioning' showed that for both groups, it was either 'Impaired Skin Integrity' or 'Risk for Skin Integrity Impairment'. This study identified a need for further refinement in the classification of nursing interventions to include those unique to home care and that for the purposes of computerization identification of the nursing activities to be included in each intervention needs to be done.

• 대한디지털의료영상학회논문지
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• 제12권1호
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• pp.5-8
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• 2010

Opened a court in February 10, 2006, a rule of safety management of the diagnosis radiation system was promulgated for safety of the radiation worker, patients and patients' family members. The purpose of this rule is to minimize the risk of being exposed to radiation during the process of handling X-ray. For this reason, we manufactured shielding device of mobile X-ray unit collimator for diminution of skin dose. Shielding device is made to a thickness of Pb 0.375mm. For portable chest radiography, we measured skin dose 50cm from center ray to 200cm at intervals of 20cm by Unfors Xi detector. As a result, a rule of safety management of the diagnosis radiation system has been strengthened. But there are exceptions, such as ER, OR, ICU to this rule. So shielding device could contribute to protect unnecessary radiation exposure and improve nation's health.

• Biomolecules & Therapeutics
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• 제32권1호
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• pp.1-12
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• 2024

Adverse drug reactions (ADRs) are an inherent aspect of drug use. While approximately 80% of ADRs are predictable, immune system-mediated ADRs, often unpredictable, are a noteworthy subset. Skin-related ADRs, in particular, are frequently unpredictable. However, the wide spectrum of skin manifestations poses a formidable diagnostic challenge. Comprehending the pathomechanisms underlying ADRs is essential for accurate diagnosis and effective management. The skin, being an active immune organ, plays a pivotal role in ADRs, although the precise cutaneous immunological mechanisms remain elusive. Fortunately, clinical manifestations of skin-related ADRs, irrespective of their severity, are frequently rooted in immunological processes. A comprehensive grasp of ADR morphology can aid in diagnosis. With the continuous development of new pharmaceuticals, it is noteworthy that certain drugs including immune checkpoint inhibitors have gained notoriety for their association with ADRs. This paper offers an overview of immunological mechanisms involved in cutaneous ADRs with a focus on clinical features and frequently implicated drugs.

• Annals of Clinical Neurophysiology
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• 제14권1호
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• pp.1-6
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• 2012

Low back pain is a common clinical condition with heterogeneous causes and challenges to manage. High prevalence and numerous assessments result in an enormous socioeconomic burden. Clinician must conduct efficient and stepwise evaluation process to rule out serious spinal pathology, neurologic involvement, and identify risk factors for chronicity. The process can be achieved through the focused history taking and physical examination. Certain factors related to serious spinal pathology include age (>50 years), trauma, unexplained fever, recent urinary or skin infection, unrelenting night or rest pain, unexplained weight loss, osteoporosis, immunosuppression, steroid use, and widespread neurological symptoms. In non-specific low back pain, diagnostic imaging and laboratory studies are often unnecessary and can disturb an appropriate management. For the management of acute low back pain, patient education and medication such as acetaminophen, non-steroidal anti-inflammatory drugs, and muscle relaxants are recommended. For chronic low back pain, behavior therapy, back exercise, and spinal manipulation are beneficial. The evidence based approach could improve success rate of management, result in prevention of acute low back pain from being chronic intractable pain.

• 한국컴퓨터정보학회논문지
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• 제27권9호
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• pp.191-203
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• 2022

화장품 및 뷰티산업에서 고객 맞춤형 제품과 서비스를 제공하는 것은 주요 기술 트렌드이고, 피부상태 진단과 관리는 중요한 필수기능이다. 고객의 요구 수준은 더욱더 높아지고 있으며 이에 대한 다양하고 섬세한 고민과 요구 사항이 소셜미디어 커뮤니티에서 활발하게 다루어지고 있다. 소셜미디어 상의 이미지는 매우 다양하고 비정형적이므로 피부상태 진단 및 관리에 필요한 체계적인 피부 이미지 식별을 위한 시스템이 필요하다. 본 논문에서는 소셜미디어 인스타그램에서 수집한 빅데이터로부터 피부 이미지 데이터를 지능적으로 식별하고, 피부상태 진단 및 관리를 위한 정형화된 피부 샘플 데이터를 추출하는 시스템을 개발하였다. 본 논문에서 제안한 시스템은 빅데이터수집분석단계, 피부이미지분석단계, 훈련데이터준비단계, 인공신경망훈련단계, 피부이미지식별단계로 구성된다. 빅데이터수집분석단계에서는 인스타그램으로부터 빅데이터를 수집하고 피부 상태 진단 및 관리를 위한 이미지 정보를 분석결과로 저장한다. 피부이미지분석단계에서는 전통적인 이미지 처리 기법을 사용하여 피부 이미지의 평가 및 분석 결과를 획득한다. 훈련데이터준비단계에서는 피부이미지 분석결과로부터 피부 샘플데이터를 추출하여 훈련데이터를 준비하였다. 그리고 인공신경망훈련단계에서는 이 훈련데이터를 사용하여 지능적으로 피부 이미지 유형을 예측하는 인공신경망 AnnSampleSkin을 단계별 고도화와 훈련을 통해 모델을 완성하였다. 피부이미지식별단계에서는 소셜미디어로부터 수집된 이미지에 대해 피부샘플을 추출하고, 훈련된 인공신경망 AnnSampleSkin의 이미지 유형 예측 결과들을 통합하여 최종 피부 이미지 유형을 지능적으로 식별한다. 본 논문에서 제안된 피부이미지식별 방법은 약 92% 이상의 높은 피부 이미지 식별 정확도를 나타내고 있고, 정형화된 피부 샘플 이미지 빅데이터를 제공할 수 있게 되었다. 추출된 피부샘플 세트는 피부 상태를 진단하고 관리하는데 매우 효율적이고 유용한 정형화된 피부 이미지 데이터로 사용될 것으로 기대된다.

• Archives of Plastic Surgery
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• 제41권5호
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• pp.500-504
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• 2014

Background Skin cancer is the most prevalent cancer by organ type and referral accuracy is vital for diagnosis and management. The British Association of Dermatologists (BAD) and literature highlight the importance of accurate skin lesion examination, diagnosis and educationally-relevant studies. Methods We undertook a review of the relevant literature, a national audit of skin lesion description standards and a study of speciality training influences on these descriptions. Questionnaires (n=200), with pictures of a circular and an oval lesion, were distributed to UK dermatology/plastic surgery consultants and speciality trainees (ST), general practitioners (GP), and medical students (MS). The following variables were analysed against a pre-defined 95% inclusion accuracy standard: site, shape, size, skin/colour, and presence of associated scars. Results There were 250 lesion descriptions provided by 125 consultants, STs, GPs, and MSs. Inclusion accuracy was greatest for consultants over STs (80% vs. 68%; P<0.001), GPs (57%) and MSs (46%) (P<0.0001), for STs over GPs (P<0.010) and MSs (P<0.0001) and for GPs over MSs (P<0.010), all falling below audit standard. Size description accuracy sub-analysis according to circular/oval dimensions was as follows: consultants (94%), GPs (80%), STs (73%), MSs (37%), with the most common error implying a quadrilateral shape (66%). Addressing BAD guidelines and published requirements for more empirical performance data to improve teaching methods, we performed a national audit and studied skin lesion descriptions. To improve diagnostic and referral accuracy for patients, healthcare professionals must strive towards accuracy (a circle is not a square). Conclusions We provide supportive evidence that increased speciality training improves this process and propose that greater focus is placed on such training early on during medical training, and maintained throughout clinical practice.