Zobrazeno 1 - 10
of 37
pro vyhledávání: '"Sun-Young Jeon"'
Publikováno v:
BioMedical Engineering OnLine, Vol 21, Iss 1, Pp 1-22 (2022)
Abstract Background To obtain phase-contrast X-ray images, single-grid imaging systems are effective, but Moire artifacts remain a significant issue. The solution for removing Moire artifacts from an image is grid rotation, which can distinguish betw
Externí odkaz:
https://doaj.org/article/c0bfcb60fdb14e85812bb915400aeae5
Publikováno v:
Epidemiology and Health, Vol 39 (2017)
This study aims to provide a systematical introduction of age-period-cohort (APC) analysis to South Korean readers who are unfamiliar with this method (we provide an extended version of this study in Korean). As health data in South Korea has substan
Externí odkaz:
https://doaj.org/article/a47f8eac0a8a4b63bfa22a92168de483
Autor:
Sun-young Jeon
Publikováno v:
Christian Social Ethics. 55:369-400
Autor:
Sun-Young Jeon, Han-Ik Jo
Publikováno v:
KOREAN JOURNAL OF YOUTH STUDIES. 29:87-112
Autor:
Sun Young Jeon
Publikováno v:
Peace and Unification Review. 1:69-98
Autor:
sun-young Jeon
Publikováno v:
Han Mun Hak Bo. 46:5-42
Publikováno v:
Medical Imaging 2023: Physics of Medical Imaging.
Autor:
Sachin J. Shah, Carl van Walraven, Sun Young Jeon, W. John Boscardin, FD Richard Hobbs, Stuart Connolly, Michael Ezekowitz, Kenneth E. Covinsky, Margaret C. Fang, Daniel E. Singer
Publikováno v:
medRxiv
ImportancePatients with atrial fibrillation have a high rate of all-cause mortality that is only partially attributable to vascular outcomes. While the competing risk of death affects expected anticoagulant benefit, guidelines do not account for the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec5dacac0f1d44212a03b2c729ba1380
https://doi.org/10.1101/2023.02.10.23285303
https://doi.org/10.1101/2023.02.10.23285303
Autor:
Bocheng, Jing, W John, Boscardin, W James, Deardorff, Sun Young, Jeon, Alexandra K, Lee, Anne L, Donovan, Sei J, Lee
Publikováno v:
Med Care
BACKGROUND: It is unclear whether machine learning methods yield more accurate electronic health record (EHR) prediction models compared to traditional regression methods. OBJECTIVE: To compare machine learning and traditional regression models for 1
Autor:
Sun Young Jeon
Publikováno v:
Christian Social Ethics. 51:347-373