Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Joon-Myoung Kwon"'
Autor:
Ki-Hyun Jeon, Hak Seung Lee, Sora Kang, Jong-Hwan Jang, Yong-Yeon Jo, Jeong Min Son, Min Sung Lee, Joon-myoung Kwon, Ju-Seung Kwun, Hyoung-Won Cho, Si-Hyuck Kang, Wonjae Lee, Chang-Hwan Yoon, Jung-Won Suh, Tae-Jin Youn, In-Ho Chae
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Electrocardiogram (ECG) changes after primary percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients are associated with prognosis. This study investigated the feasibility of predicting left v
Externí odkaz:
https://doaj.org/article/442a9d28a0a042669d92236d8d2b19c7
Autor:
Tae Gun Shin, Youngjoo Lee, Kyuseok Kim, Min Sung Lee, Joon-myoung Kwon, on behalf of the ROMIAE study group
Publikováno v:
Clinical and Experimental Emergency Medicine, Vol 10, Iss 4, Pp 438-445 (2023)
Objective Based on the development of artificial intelligence (AI), an emerging number of methods have achieved outstanding performances in the diagnosis of acute myocardial infarction (AMI) using an electrocardiogram (ECG). However, AI-ECG analysis
Externí odkaz:
https://doaj.org/article/25825a2a8c974825bdccb7917dd3af45
Autor:
Changi Kim, Joon-myoung Kwon, Jiyeong Lee, Hongju Jo, Dowan Gwon, Jae Hoon Jang, Min Kyu Sung, Sang Won Park, Chulho Kim, Mi-Young Oh
Publikováno v:
Heliyon, Vol 10, Iss 10, Pp e31000- (2024)
Abstracts: Objective: Most prognostic indexes for ischemic stroke mortality lack radiologic information. We aimed to create and validate a deep learning-based mortality prediction model using brain diffusion weighted imaging (DWI), apparent diffusion
Externí odkaz:
https://doaj.org/article/a1cae7cab7774699a54045a68b3b380d
Autor:
Joon-myoung Kwon, Ye Rang Lee, Min-Seung Jung, Yoon-Ji Lee, Yong-Yeon Jo, Da-Young Kang, Soo Youn Lee, Yong-Hyeon Cho, Jae-Hyun Shin, Jang-Hyeon Ban, Kyung-Hee Kim
Publikováno v:
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, Vol 29, Iss 1, Pp 1-12 (2021)
Abstract Background Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requires immediate management, screening for the occurrence of sepsis is difficult. Herein, we pro
Externí odkaz:
https://doaj.org/article/4ccf3f6418274c508c212847db4718ea
Autor:
Junsang Yoo, Jeonghoon Lee, Ji Young Min, Sae Won Choi, Joon-myoung Kwon, Insook Cho, Chiyeon Lim, Mi Young Choi, Won Chul Cha
Publikováno v:
Journal of Medical Internet Research, Vol 24, Iss 7, p e37928 (2022)
BackgroundA clinical decision support system (CDSS) is recognized as a technology that enhances clinical efficacy and safety. However, its full potential has not been realized, mainly due to clinical data standards and noninteroperable platforms. Ob
Externí odkaz:
https://doaj.org/article/b490ab3b6bd541239dbfe9d6f2a1407d
Autor:
Younghoon Cho, Joon-myoung Kwon, Kyung-Hee Kim, Jose R. Medina-Inojosa, Ki-Hyun Jeon, Soohyun Cho, Soo Youn Lee, Jinsik Park, Byung-Hee Oh
Publikováno v:
Scientific Reports, Vol 10, Iss 1, Pp 1-10 (2020)
Abstract Rapid diagnosis of myocardial infarction (MI) using electrocardiography (ECG) is the cornerstone of effective treatment and prevention of mortality; however, conventional interpretation methods has low reliability for detecting MI and is dif
Externí odkaz:
https://doaj.org/article/9929d36a5ebe44cd8f13f0d280c39c94
Publikováno v:
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, Vol 28, Iss 1, Pp 1-10 (2020)
Abstract Background In-hospital cardiac arrest is a major burden in health care. Although several track-and-trigger systems are used to predict cardiac arrest, they often have unsatisfactory performances. We hypothesized that a deep-learning-based ar
Externí odkaz:
https://doaj.org/article/a368b754d7f24bd68b01aa012753a517
Autor:
Da-Young Kang, Kyung-Jae Cho, Oyeon Kwon, Joon-myoung Kwon, Ki-Hyun Jeon, Hyunho Park, Yeha Lee, Jinsik Park, Byung-Hee Oh
Publikováno v:
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, Vol 28, Iss 1, Pp 1-8 (2020)
Abstract Background In emergency medical services (EMSs), accurately predicting the severity of a patient’s medical condition is important for the early identification of those who are vulnerable and at high-risk. In this study, we developed and va
Externí odkaz:
https://doaj.org/article/73f376706b6e44b59c80f3bf9286f0d1
Autor:
Yong-Yeon Jo, Jong-Hwan Jang, Joon-Myoung Kwon, Hyung-Chul Lee, Chul-Woo Jung, Seonjeong Byun, Han-Gil Jeong
Publikováno v:
PLoS ONE, Vol 17, Iss 8, p e0272055 (2022)
To develop deep learning models for predicting Interoperative hypotension (IOH) using waveforms from arterial blood pressure (ABP), electrocardiogram (ECG), and electroencephalogram (EEG), and to determine whether combination ABP with EEG or CG impro
Externí odkaz:
https://doaj.org/article/181000ed5d444a1eb047be87bbf50b23
Autor:
Joon‐myoung Kwon, Min‐Seung Jung, Kyung‐Hee Kim, Yong‐Yeon Jo, Jae‐Hyun Shin, Yong‐Hyeon Cho, Yoon‐Ji Lee, Jang‐Hyeon Ban, Ki‐Hyun Jeon, Soo Youn Lee, Jinsik Park, Byung‐Hee Oh
Publikováno v:
Annals of Noninvasive Electrocardiology, Vol 26, Iss 3, Pp n/a-n/a (2021)
Abstract Introduction The detection and monitoring of electrolyte imbalance is essential for appropriate management of many metabolic diseases; however, there is no tool that detects such imbalances reliably and noninvasively. In this study, we devel
Externí odkaz:
https://doaj.org/article/386a234b95b248d8a2334ef8cb560a9b