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- 저자 : 최세헌(Se-Heon Choi) (검색결과 4 건)
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Pain Disability of Orofacial Pain Patients
최세헌,김기석,김미은,Choi, Se-Heon,Kim, Ki-Suk,Kim, Mee-Eun Korean Academy of Orofacial Pain and Oral Medicine 2009 Journal of Oral Medicine and Pain Vol.34 No.2
As Pain is a comprehensive, biopsy chosocial phenomenon, improved understanding and successful management of pain need assessment of health-related quality of life and psychological states. The purpose of this study was to evaluate pain severity and pain-related interference to daily lives for patients with non-dental, orofacial pain(OFP) and a possible relation of OFP with psychological morbidity. Relation with such factors as gender, age, pain duration and diagnosis was also assessed. Inclusion criteria was all new patients with non-dental OFP attending the oral medicine.orofacial pain clinic of Dankook University Dental Hospital over 3 months' period, who completed the questionnaires of the Brief Pain Inventory (BPI) and Hospital Anxiety and Depression Scale (HADS). Prior to the first consultation, the patients were asked to fill out the questionnaire in the waiting room and were diagnosed through consultation and clinical examination. Total subjects were 163 with M:F ratio of 1:1.5 and mean age of 34.6${\pm}$17.7 years. Mean duration of pain was 13.3${\pm}$26.2 months and all patients were divided into; Trigeminal Neuralgia group (TN, N=8), Neuropathic Pain group (NeP, N=9), Persistent Idiopathic Facial Pain group (PIFP, N=8), and Temporomandibular Disorders group (TMD, N=138), subdivided into muscle problem (TMD-m, N=73), joint problem (TMD-j, N=24) and muscle-joint combined problem (TMD-c, N=41). OFP patients showed moderate pain severity and moderate pain-related interference. There was no gender difference in overall pain severity and interference and levels of anxiety and depression. Elderly patients aged ${\geq}$ 60 years showed higher pain severity (p<0.05). Patients with chronic pain ${\geq}$ 3 months reported more increased level of anxiety and depression than those with acute pain (p<0.05). Compared to TMD patients, patients with TN, NeP and PIFP suffered from higher level of pain and pain-related interference and reported higher level of anxiety and depression (p<0.05). Pain interference was closely correlated with their pain severity and with psychometric properties such as anxiety and depression. Pain severity was weakly correlated with levels of anxiety and depression. The results suggest a need for psychosocial assessment and support for successful management of OFP in addition to control of pain itself.
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최세헌(Se-Heon Choi),황동환(Dong-Hwan Hwang),김도현(Do-Hyeon Kim),박소현(So-Hyeon Bak),김윤(Yoon Kim) 한국컴퓨터정보학회 2021 韓國컴퓨터情報學會論文誌 Vol.26 No.12
본 논문에서는 컴퓨터 단층촬영(CT) 이미지를 이용한 합성곱 신경망(CNN)을 기반의 골감소증 및 골다공증 예측 모델을 제안한다. 기존의 CNN은 단일 CT 이미지에서 예측에 중요한 지역정보를 활용하지 못하다는 문제가 있다. 본 논문에서 이를 해결하고자 CT 이미지를 정규화하여 질감 정보가 다른 두 개의 이미지로 변환하고, 해당 이미지를 활용한 한 쌍의 신경망 네트워크를 제안한다. 동일한 구조를 가진 네트워크 각각의 신경망은 질감 정보가 다른 이미지를 입력으로 사용하고 비유사성 손실함수를 통해 다른 정보를 학습한다. 최종적으로 제안 모델은 중요한 지역정보를 포함한 단일 CT 이미지의 다양한 특징 정보를 학습하며, 이를 앙상블하여 골감소증 및 골다공증 예측 정확도를 높인다. 실험 결과를 통해 제안 모델의 정확도 77.11%를 확인할 수 있으며 Grad-CAM을 이용하여 모델이 바라보는 특징을 확인할 수 있다. In this paper, we propose a prediction model for osteopenia and osteoporosis based on a convolutional neural network(CNN) using computed tomography(CT) images. In a single CT image, CNN had a limitation in utilizing important local features for diagnosis. So we propose a compound model which has two identical structures. As an input, two different texture images are used, which are converted from a single normalized CT image. The two networks train different information by using dissimilarity loss function. As a result, our model trains various features in a single CT image which includes important local features, then we ensemble them to improve the accuracy of predicting osteopenia and osteoporosis. In experiment results, our method shows an accuracy of 77.11% and the feature visualize of this model is confirmed by using Grad-CAM.
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