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2020 연구자 정보 (182 / 997)

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Author Name 제1저자 여부 ⓘ 교신저자 여부 ⓘ Address ResearcherID ORCID Paper Title WoS Edition 최상위 JCR(%) WoS Category Related Email
Choi, G. Y.
(Choi, GY) ⓘ 		Soonchunhyang Univ, Seoul Hosp, Coll Med, Seoul, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Choi, S-J
(Choi, SJ) ⓘ 		제1저자 Sungkyunkwan Univ, Samsung Med Ctr, Sch Med, Seoul, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Choi, S. K.
(Choi, SK) ⓘ 		Catholic Univ Korea, Coll Med, Seoul, South Korea
Gyeongsang Natl Univ, Jinju 52828, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis
[JCR상위 19.0] Study of B → pππ
[JCR상위 7.6] Observation of the Radiative Decays of Υ(1S) to χc1 ⓘ 		SCIE ⓘ 7.6 OBSTETRICS & GYNECOLOGY
ASTRONOMY & ASTROPHYSICS;PHYSICS, PARTICLES & FIELDS
PHYSICS, MULTIDISCIPLINARY ⓘ 		kkyj@ewha.ac.kr; ⓘ
Dayan, Ittai
(Dayan, I) ⓘ 		MGH & BWH Ctr Clin Data Sci, Boston, MA 02114 USA ⓘ
ⓘ 		0000-0003-4024-8740
Dayan, Ittai ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Ebrahimian, Shadi
(Ebrahimian, S) ⓘ 		Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ AAF-7064-2019
Ebrahimian, Shadi ⓘ
ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Fang, Wei
(Fang, W) ⓘ 		Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ CAA-1842-2022
Fang, Wei ⓘ
ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Gong, Kuang
(Gong, K) ⓘ 		Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ W-6203-2019
Gong, Kuang ⓘ
ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Homayounieh, Fatemeh
(Homayounieh, F) ⓘ 		Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Hur, S. E.
(Hur, SE) ⓘ 		Konyang Univ Hosp, Daejeon, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Hwang, H. S.
(Hwang, HS) ⓘ 		Konkuk Univ, Res Inst Med Sci, Sch Med, Seoul, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Kalra, Mannudeep K.
(Kalra, MK) ⓘ 		교신저자 Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ LXW-4237-2024
Kalra, Mannudeep ⓘ
ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Kil, K.
(Kil, K) ⓘ 		Catholic Univ Korea, Yeouido St Marys Hosp, Seoul, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Kim, Kyungsang
(Kim, K) ⓘ 		Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA ⓘ
ⓘ 		0000-0002-9860-072X
Kim, Kyungsang ⓘ 		[JCR상위 7.8] Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels ⓘ SCIE ⓘ 7.8 COMPUTER SCIENCE, INFORMATION SYSTEMS;COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS;MATHEMATICAL & COMPUTATIONAL BIOLOGY;MEDICAL INFORMATICS ⓘ dwu6@mgh.harvard.edu;kgong@mgh.harvard.edu;carru@mgh.harvard.edu;fhomayounieh@mgh.harvard.edu;bbizzo@mgh.harvard.edu;varun.buch@mgh.harvard.edu;hren2@mgh.harvard.edu;kkim24@mgh.harvard.edu;nir.neumark@mgh.harvard.edu;pxu3@mgh.harvard.edu;zliu40@mgh.harvard.edu;wfang3@mgh.harvard.edu;nxie@mgh.harvard.edu;wytak@knu.ac.kr;psy@knu.ac.kr;deblue00@naver.com;kmggood111@naver.com;jgpark@ynu.ac.kr;profcarriero@virgilio.it;lucasabamd@gmail.com;mahsami141@gmail.com;rosa.babaei@gmail.com;hadi.karimimobin@gmail.com;sebrahimian@mgh.harvard.edu;idayan@partners.org;mkalra@mgh.harvard.edu;quanzheng@mgh.harvard.edu; ⓘ
Kim, S-C
(Kim, SC) ⓘ 		Pusan Natl Univ, Coll Med, Pusan, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
Kim, S. M.
(Kim, SM) ⓘ 		Seoul Natl Univ, Seoul Metropolitan Govt, Boramae Med Ctr, Coll Med, Seoul, South Korea ⓘ
ⓘ
ⓘ 		[JCR상위 7.8] Vaginal compared with intramuscular progestogen for preventing preterm birth in high-risk pregnant women (VICTORIA study): a multicentre, open-label randomised trial and meta-analysis ⓘ SCIE ⓘ 7.8 OBSTETRICS & GYNECOLOGY ⓘ kkyj@ewha.ac.kr; ⓘ
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