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2020 연구자 정보 (183 / 997)

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Author Name 제1저자 여부 교신저자 여부 Address ResearcherID ORCID Paper Title WoS Edition 최상위 JCR(%) WoS Category Related Email
Kwak, D. W.
(Kwak, DW)
Ajou Univ, Sch Med, Suwon, 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;
Kwon, J-Y
(Kwon, JY)
Yonsei Univ, Inst Womens Life Med Sci, Coll Med, Seoul, South Korea
0000-0003-3009-6325
Kwon, Ja-Young
[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;
Lee, K. A.
(Lee, KA)
Kyung Hee Univ, 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;
Liu, Zhiyuan
(Liu, ZY)
Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA I-2233-2014
Liu, Zhiyuan

[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;
Masjedi, Mahsa
(Masjedi, M)
Shahid Beheshti Hosp, Dept Radiol, Kashan 00000, Iran

[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;
Mobin, Hadi Karimi
(Mobin, HK)
Iran Univ Med Sci, Firoozgar Hosp, Dept Radiol, Tehran, Iran

[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;
Na, S.
(Na, S)
Kangwon Natl Univ, Kangwon Natl Univ Hosp, Sch Med, Chunchon, South Korea AAE-3929-2022
Na, Sunghun

[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;
Neumark, Nir
(Neumark, N)
MGH & BWH Ctr Clin Data Sci, 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;
Oh, K. Y.
(Oh, KY)
Eulji Univ, Sch Med, 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;
Ren, Hui
(Ren, H)
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;
Saba, Luca
(Saba, L)
Azienda Osped Univ Policlin Cagliari, Radiol, I-09124 Cagliari, Italy

[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;
Shim, J-Y
(Shim, JY)
Univ Ulsan, Asan Med Ctr, Coll Med, Seoul, South Korea C-5526-2012
Shim, Jae-Yoon

[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;
Talari, Hamidreza
(Talari, H)
Shahid Beheshti Hosp, Dept Radiol, Kashan 00000, Iran

[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;
Wu, Dufan
(Wu, DF)
제1저자 Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA AFZ-1956-2022
Wu, Dufan
0000-0002-3204-3502
Wu, Dufan
[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;
Xie, Nuobei
(Xie, NB)
Massachusetts Gen Hosp, Dept Radiol, Boston, MA 02114 USA AAG-9180-2021
Xie, Nuobei

[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;
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