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ÀÛ¼ºÀÚ »ç¹«±¹ ÀÛ¼ºÀÏ 2022-03-25 Á¶È¸¼ö 1567


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O1. Á¦¸ñ: Comprehensive Comparative Assessment of the Whole Slide Images of Cytologic Samples for Quality Assurance Program in Korea

¼º¸í: Yosep Chong1,*, Soon Auck Hong2, Hoon Kyu Oh3, Soo Jin Jung4, Bo-Sung Kim5, Ji Yun Jeong6, Ho Chang Lee7, Gyungyub Gong8, The Committee of Quality Improvement of Korean Society for Cytopathology

¼Ò¼Ó: 1Department of Hospital Pathology, The Catholic University of Korea College of Medicine, Seoul; 2Department of Pathology, Chung-Ang University College of Medicine, Seoul; 3Department of Pathology, Daegu Catholic University School of Medicine, Daegu; 4Department of Pathology, Inje University Busan Paik Hospital, Busan; 5Department of Pathology, Green Cross Laboratories, Yongin; 6Department of Pathology, Kyungpook National University Chilgok Hospital, School of Medicine, Kyungpook National University, Daegu; 7Department of Pathology, Chungbuk National University College of Medicine, Cheongju; 8Department of Pathology, Asan Medical Center, University of Ulsan Col lege of Medicine, Seoul, Republic of Korea.

 

O2. Á¦¸ñ: Establishment of Non-face-to-face Image Training Platform for Korean  Association of Cytotechnologists (KAC)

¼º¸í: Youngjoo Kim, C.T1., Kang Jeong-Eun, C.T2., Gyeong-Su Ko, C.T3., Young-Jae Oh1, C.T., Kwang Pyo Hong1, C.T., Ji Yoon Eum1, C.T., Kyung Hee Shon1, C.T., Myong Ja Jeon1, C.T., Eung-Soo Eo1, C.T., Jae-Nam Ko1, C.T., Gyungyub Gong1, M.D., Kyung-Ja Cho1, M.D.

¼Ò¼Ó: 1Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea, 2Department of Pathology Yonsei University College of Medicine, 3Department of Pathology Samsung Medical Center

 


O3. Á¦¸ñ: Deep learning-based detection of metastatic ovarian cancer from ascitic fluids

¼º¸í: Kwangil Yim1 , Jamshid ABDUL-GHAFAR1, Kyung Jin SEO1, Ok Ran Shin 1, Gisu HWANG2, Sohyun JEONG2, Gyungyub GONG3*, Nam Hoon CHO4, Chong woo YOO5, and Yosep CHONG1

¼Ò¼Ó: 1Department of Hospital Pathology, The Catholic University of Korea College of Medicine, Seoul; 2AI Team, DeepNoid Inc., Seoul; 3Department of Pathology, Asan Medical Center, Seoul; 4Department of Pathology, Yonsei University College of Medicine, Seoul; 5Department of Pathology, National Cancer Center, Ilsan, Gyeonggi-do, REPUBLIC OF KOREA

 


O4. Á¦¸ñ: Feasibility of a deep learning algorithm to distinguish malignancy in pleural fluids cytology specimens

¼º¸í: Kyung Jin SEO1 , Kwangil Yim1, Jamshid ABDUL-GHAFAR1, Ok Ran Shin 1, Gisu HWANG2, Sohyun JEONG2, Gyungyub GONG3, Nam Hoon CHO4, Chong woo YOO5, and Yosep CHONG1*

¼Ò¼Ó: 1Department of Hospital Pathology, The Catholic University of Korea College of Medicine, Seoul; 2AI Team, DeepNoid Inc., Seoul; 3Department of Pathology, Asan Medical Center, Seoul; 4Department of Pathology, Yonsei University College of Medicine, Seoul; 5Department of Pathology, National Cancer Center, Ilsan, Gyeonggi-do, REPUBLIC OF KOREA

 


O5. Á¦¸ñ: Applying Shorr Staining Method in Rapid On-site Evaluation for Solid Pancreatic Lesions: a Pilot Study

¼º¸í: Hee Young Na1 , Jong-Chan Lee2, Jin-Hyeok Hwang2, Jaihwan Kim2

¼Ò¼Ó 1Department of Pathology, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea 2 Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea

 


O6. Á¦¸ñ: Improvement of Diagnostic Accuracy of Pancreas EUS-guided needle biopsy by Liquid-Based Preparation Cytology

¼º¸í: Ji Yoon Eum, C.T., Youngjoo Kim, C.T., Kwang Pyo Hong, C.T., Hwajeong Shin, C.T., Kyung Hee Shon, C.T.,Myong Ja Jeon, C.T., Eung-Soo Eo, C.T., Young-Jae Oh, C.T., Jae-Nam Ko, C.T., Seung-Mo Hong, M.D., Gyungyub Gong, M.D., Kyung-Ja Cho, M.D.

¼Ò¼Ó: Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea





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