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S

Sung Yeon Hwang

Samsung Medical Center
H指数:24
被引数:2,127

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荣誉奖项

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Interpretable Machine Learning Model for Predicting Sepsis and Septic Shock Among Patients with Documented Fever at Emergency Department Triage Using Patients’ Historical Data

基于患者历史数据的急诊分诊中用于预测发热患者败血症和脓毒性休克的可解释机器学习模型

Journal of Medical Systems
IF5.7
2026-07-210
OAAI
Seung Jin Maeng; Ye Rim Lee; Se Uk Lee; Jae Yong Yu; Jung Won Choi; Guntak Lee; Jong Eun Park; Tae Gun Shin; Sung Yeon Hwang; Hee Yoon; Won Chul Cha; Taerim Kim; Minha Kim; Hansol Chang; Sejin Heo
AI-driven carotid artery compressibility assessment via point-of-care ultrasound for blood pressure estimation in critically ill and post-resuscitation patients: a prospective observational study

基于人工智能驱动、通过床旁超声进行颈动脉可压缩性评估，以估算危重及复苏后患者的血压：一项前瞻性观察性研究

Critical Care
IF9.3
2025-11-280
OAAI
Seung Jin Maeng; Subin Park; Ik Joon Jo; Guntak Lee; Sung Yeon Hwang; Myung Jin Chung; Jihyeon Kim; Hakje Yoo; Hee Yoon
From prediction to action: a retrospective observational study on the real-world implementation of Critical Interventions (CrIs), an AI-based clinical decision support system changing clinical behavior in the emergency department

从预测到行动：一项关于基于AI的临床决策支持系统Critical Interventions（CrIs）在急诊科真实世界实施情况的回顾性观察研究，该系统改变了临床行为

BMC Medical Informatics and Decision Making
IF3.8
2025-11-040
OAAI
Hansol Chang; Jae Yong Yu; Hyunjung Park; Yee Jun Song; Sejin Heo; Jong Eun Park; Gun Tak Lee; Se Uk Lee; Taerim Kim; Hee Yoon; Sung Yeon Hwang; Won Chul Cha
Scale to predict risk for refractory septic shock based on a hybrid approach using machine learning and regression modeling

基于机器学习和回归建模混合方法预测难治性脓毒症休克风险的量表

EMERGENCIAS
IF6.3
2024-12-192
PRE
Heo, Sejin; Jeong, Daun; Choi, Minyoung; Kim, Inkyu; Kim, Minha; Lee, Ye Rim; Ko, Byuk Sung; Ryoo, Seung Mok; Han, Eunah; Chang, Hyunglan; Yune, Chang June; Lee, Hui Jai; Suh, Gil Joon; Choi, Sung-Hyuk; Chung, Sung Phil; Lim, Tae Ho; Kim, Won Young; Kim, Kyuseok; Hwang, Sung Yeon; Park, Jong Eun; Lee, Gun Tak; Shin, Tae Gun
Artificial intelligence-based evaluation of carotid artery compressibility via point-of-care ultrasound in determining the return of spontaneous circulation during cardiopulmonary resuscitation

基于人工智能的通过实时超声评估颈动脉可压缩性，以确定心肺复苏期间的自主循环恢复

RESUSCITATION
IF4.6
2024-09-011
OAAI
Park, Subin; Yoon, Hee; Kang, Soo Yeon; Jo, Ik Joon; Heo, Sejin; Chang, Hansol; Park, Jong Eun; Lee, Guntak; Kim, Taerim; Hwang, Sung Yeon; Park, Soyoung; Chung, Myung Jin

研究方向

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T
Tae Gun Shin
H 指数:30论文数:215被引数:3,651
H
Hee Yoon
H 指数:20论文数:96被引数:1,280
J
Jong Eun Park
H 指数:12论文数:70被引数:598
I
Ik Joon Jo
H 指数:31论文数:157被引数:3,683
G
Gun Tak Lee
H 指数:11论文数:63被引数:444
W
Won Chul
H 指数:31论文数:270被引数:3,641
S
Se Uk Lee
H 指数:12论文数:67被引数:560
T
Taerim Kim
H 指数:12论文数:84被引数:476
M
Min Seob Sim
H 指数:26论文数:133被引数:2,494
H
Hansol Chang
H 指数:9论文数:53被引数:241