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2021 연구성과별 연구자 정보 (525 / 2991)

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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma Shin, Seunghwan Shin, S 6 Lunit Inc, Seoul 06241, South Korea skyblue718@skku.edu;brian.j.aum@lunit.io;shlee119@skku.edu;hkts@skku.edu;jkimsmc@skku.edu;ssh@lunit.io;jyjeong@knu.ac.kr;ock.chanyoung@lunit.io;hoyunlee@skku.edu;
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma Jeong, Ji Yun Jeong, JY 7 Kyungpook Natl Univ, Chilgok Hosp, Dept Pathol, Sch Med, Daegu 41404, South Korea skyblue718@skku.edu;brian.j.aum@lunit.io;shlee119@skku.edu;hkts@skku.edu;jkimsmc@skku.edu;ssh@lunit.io;jyjeong@knu.ac.kr;ock.chanyoung@lunit.io;hoyunlee@skku.edu;
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma Ock, Chan-Young Ock, CY 8 교신저자 Lunit Inc, Seoul 06241, South Korea 0000-0002-6755-9728 Ock, Chan-Young skyblue718@skku.edu;brian.j.aum@lunit.io;shlee119@skku.edu;hkts@skku.edu;jkimsmc@skku.edu;ssh@lunit.io;jyjeong@knu.ac.kr;ock.chanyoung@lunit.io;hoyunlee@skku.edu;
Deep Learning Analysis of CT Images Reveals High-Grade Pathological Features to Predict Survival in Lung Adenocarcinoma Lee, Ho Yun Lee, HY 9 교신저자 Sungkyunkwan Univ, Samsung Med Ctr, Dept Radiol, Sch Med SKKU SOM, Seoul 06351, South Korea D-6086-2012 Lee, Ho Yun 0000-0001-9960-5648 Lee, Ho Yun skyblue718@skku.edu;brian.j.aum@lunit.io;shlee119@skku.edu;hkts@skku.edu;jkimsmc@skku.edu;ssh@lunit.io;jyjeong@knu.ac.kr;ock.chanyoung@lunit.io;hoyunlee@skku.edu;
Deep learning based prediction of extraction difficulty for mandibular third molars Yoo, Jeong-Hun Yoo, JH 1 Wonkwang Univ, Daejeon Dent Hosp, Coll Dent, Dept Oral & Maxillofacial Surg, Daejeon, South Korea 0000-0002-4966-396X Yoo, Jeong-Hun bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Yeom, Han-Gyeol Yeom, HG 2 Wonkwang Univ, Daejeon Dent Hosp, Coll Dent, Dept Oral & Maxillofacial Radiol, Daejeon, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Shin, WooSang Shin, W 3 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Shin, WooSang Shin, W 3 Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Yun, Jong Pil Yun, JP 4 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Lee, Jong Hyun Lee, JH 5 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Lee, Jong Hyun Lee, JH 5 Kyungpook Natl Univ, Coll IT Engn, Sch Elect Engn, Daegu, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Jeong, Seung Hyun Jeong, SH 6 Korea Inst Ind Technol KITECH, Safety Syst Res Grp, Gyongsan, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Lim, Hun Jun Lim, HJ 7 Wonkwang Univ, Daejeon Dent Hosp, Coll Dent, Dept Oral & Maxillofacial Surg, Daejeon, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Lee, Jun Lee, J 8 Wonkwang Univ, Daejeon Dent Hosp, Coll Dent, Dept Oral & Maxillofacial Surg, Daejeon, South Korea bck@wku.ac.kr;
Deep learning based prediction of extraction difficulty for mandibular third molars Kim, Bong Chul Kim, BC 9 교신저자 Wonkwang Univ, Daejeon Dent Hosp, Coll Dent, Dept Oral & Maxillofacial Surg, Daejeon, South Korea ABB-3866-2020 Kim, Bong 0000-0003-2824-0439 Kim, Bong Chul bck@wku.ac.kr;
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