http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
갑상선 유두상암의 수술 전 림프절 전이 진단에서 경부 단층 촬영과 퓨전 양전자 방출 단층 촬영 비교
정성일,강현종,유영범,Sung Il Jung,M,D,Hyun Jong Kang,M,D,and Young Bum Yoo,M,D,Ph,D 대한갑상선-내분비외과학회 2009 The Koreran journal of Endocrine Surgery Vol.9 No.3
Purpose: Lymph node metastasis is one of the most important prognostic factors for patients with papillary thyroid cancer. In this study we compared the diagnostic accuracy of neck CT with that of <SUP>18</SUP>F-FDG PET-CT for the preopera</SUP>tive evaluation of lymph node metastasis. Methods: We reviewed the medical records of 56 patients who received surgery for papillary thyroid cancer at the Department of Surgery, Konkuk University Medical Center, from August, 2006 to January, 2009. All the patients were checked with neck CT and <SUP>18</SUP>F-FDG PET-CT preoperatively for evaluating their lymph node status. Results: Neck CT showed a sensitivity of 40%, a specificity of 74.2%, a positive predictive value of 55.6%, a negative predictive value of 60.5% and an accuracy of 58.9%. <SUP>18</SUP>F-FDG PET-CT showed a sensitivity of 48%, a specificity of 80.6%, a positive predictive value of 66.7%, a negative predictive value of 65.8% and an accuracy of 66.1%. <SUP>18</SUP>F- FDG PET-CT had greater sensitivity, specificity, positive predictive value, negative predictive value and accuracy than did neck CT (P=0.02) for predicting lymph node metastasis in patients with papillary thyroid cancer. Conclusion: <SUP>18</SUP>F-FDG PET-CT can be more dependable than neck CT for preoperatively assessing lymph node metastasis in patients with papillary thyroid cancer. (Ko</SUP>rean J Endocrine Surg 2009;9:140-143)
하승인(Ha, SeungYin),유영범(Yoo, Yiung Bum),정예숙(Jung, Ye Suk) 한국서비스경영학회 2017 한국서비스경영학회 학술대회 Vol.2017 No.11
Online content service providers are using recommendation systems as part of their efforts to increase sales. The recommendation system identifies and recommends the customer "s preferred content, and it helps the customer to increase the satisfaction and the loyalty of the service by using the content suitable for the user" s taste without searching the content. In this study, we propose an algorithm for selecting recommendation contents for individual customers by using the Movie Lens data. The algorithms used in the existing recommendation systems have the disadvantage that they can not utilize contents that do not exist in the data since the important words are selected from the given data and the contents are selected based thereon. On the other hand, the Latent Dirichlet Allocation algorithm is that can utilize potential keywords that are not in the data.