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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
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Kim, Kyung Hwan Kim, KH 10 Pusan Natl Univ, Sch Med, Pusan Natl Univ Hosp, Dept Urol, Busan 49241, South Korea hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Kim, Kyung Hwan Kim, KH 10 Pusan Natl Univ Hosp, Biomed Res Inst, Busan 49241, South Korea hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Kang, Byeong Jin Kang, BJ 11 Pusan Natl Univ, Sch Med, Pusan Natl Univ Hosp, Dept Urol, Busan 49241, South Korea hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Kang, Byeong Jin Kang, BJ 11 Pusan Natl Univ Hosp, Biomed Res Inst, Busan 49241, South Korea hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Kim, Sun Woo Kim, SW 12 Deep Bio Inc, Seoul 08380, South Korea hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Ha, Hong Koo Ha, HK 13 교신저자 Pusan Natl Univ, Sch Med, Pusan Natl Univ Hosp, Dept Urol, Busan 49241, South Korea W-1873-2019 Ha, Hong hongkooha@pusan.ac.kr;
Clinical implications of deep learning based image analysis of whole radical prostatectomy specimens Ha, Hong Koo Ha, HK 13 교신저자 Pusan Natl Univ Hosp, Biomed Res Inst, Busan 49241, South Korea W-1873-2019 Ha, Hong hongkooha@pusan.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Shon, Byungeun Shon, B 1 Kyungpook Natl Univ, Sch Med, Dept Med Informat, Daegu, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Seong, Sook Jin Seong, SJ 2 Kyungpook Natl Univ, Ctr Convergence Med Res, Sch Med, Daegu, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Choi, Eun Jung Choi, EJ 3 Kyungpook Natl Univ, Sch Med, Dept Mol Med, 680 Gukchaebosang Ro, Daegu 41944, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Gwon, Mi-Ri Gwon, MR 4 Kyungpook Natl Univ, Sch Med, Dept Mol Med, 680 Gukchaebosang Ro, Daegu 41944, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Lee, Hae Won Lee, HW 5 Kyungpook Natl Univ, Sch Med, Dept Mol Med, 680 Gukchaebosang Ro, Daegu 41944, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Park, Jaechan Park, J 6 Kyungpook Natl Univ, Sch Med, Dept Neurosurg, Daegu, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Chung, Ho-Young Chung, HY 7 Kyungpook Natl Univ, Sch Med, Dept Med Informat, Daegu, South Korea yry@knu.ac.kr;
Clinical Laboratory Parameter-Driven Machine Learning for Participant Selection in Bioequivalence Studies Among Patients With Gastric Cancer: Framework Development and Validation Study Jeong, Sungmoon Jeong, S 8 Kyungpook Natl Univ, Sch Med, Dept Med Informat, Daegu, South Korea yry@knu.ac.kr;
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