Zobrazeno 1 - 10
of 40
pro vyhledávání: '"Jae Yong Yu"'
Autor:
Jae Yong Yu, Doyeop Kim, Sunyoung Yoon, Taerim Kim, SeJin Heo, Hansol Chang, Gab Soo Han, Kyung Won Jeong, Rae Woong Park, Jun Myung Gwon, Feng Xie, Marcus Eng Hock Ong, Yih Yng Ng, Hyung Joon Joo, Won Chul Cha
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Emergency departments (ED) are complex, triage is a main task in the ED to prioritize patient with limited medical resources who need them most. Machine learning (ML) based ED triage tool, Score for Emergency Risk Prediction (SERP), was prev
Externí odkaz:
https://doaj.org/article/19231b0384ed4715b51b309f4713a949
Autor:
Suncheol Heo, Eun-Ae Kang, Jae Yong Yu, Hae Reong Kim, Suehyun Lee, Kwangsoo Kim, Yul Hwangbo, Rae Woong Park, Hyunah Shin, Kyeongmin Ryu, Chungsoo Kim, Hyojung Jung, Yebin Chegal, Jae-Hyun Lee, Yu Rang Park
Publikováno v:
JMIR Medical Informatics, Vol 12, Pp e47693-e47693 (2024)
Abstract BackgroundAcute kidney injury (AKI) is a marker of clinical deterioration and renal toxicity. While there are many studies offering prediction models for the early detection of AKI, those predicting AKI occurrence using distributed research
Externí odkaz:
https://doaj.org/article/ea461c033d7041808a88999da72bd433
Autor:
Jae Yong Yu, Sejin Heo, Feng Xie, Nan Liu, Sun Yung Yoon, Han Sol Chang, Taerim Kim, Se Uk Lee, Marcus Eng Hock Ong, Yih Yng Ng, Sang Do shin, Kentaro Kajino, Wen-Chu Chiang, Won Chul Cha
Publikováno v:
The Lancet Regional Health. Western Pacific, Vol 44, Iss , Pp 100996- (2024)
Externí odkaz:
https://doaj.org/article/7f8edfbfbadb486ea4e72ff529d7478c
Autor:
Suncheol Heo, Jae Yong Yu, Eun Ae Kang, Hyunah Shin, Kyeongmin Ryu, Chungsoo Kim, Yebin Chegal, Hyojung Jung, Suehyun Lee, Rae Woong Park, Kwangsoo Kim, Yul Hwangbo, Jae-Hyun Lee, Yu Rang Park
Publikováno v:
Healthcare Informatics Research, Vol 29, Iss 3, Pp 246-255 (2023)
Objectives The objective of this study was to develop and validate a multicenter-based, multi-model, time-series deep learning model for predicting drug-induced liver injury (DILI) in patients taking angiotensin receptor blockers (ARBs). The study le
Externí odkaz:
https://doaj.org/article/3522e530e278447583fa81e8265322ea
Autor:
Suncheol Heo, Jae Yong Yu, Eun Ae Kang, Hyunah Shin, Kyeongmin Ryu, Chungsoo Kim, Yebin Chega, Hyojung Jung, Suehyun Lee, Rae Woong Park, Kwangsoo Kim, Yul Hwangbo, Jae-Hyun Lee, Yu Rang Park
Publikováno v:
Healthcare Informatics Research, Vol 30, Iss 2, Pp 168-168 (2024)
Externí odkaz:
https://doaj.org/article/8d50afee057c420d9d436c2879377639
Clinical support system for triage based on federated learning for the Korea triage and acuity scale
Autor:
Hansol Chang, Jae Yong Yu, Geun Hyeong Lee, Sejin Heo, Se Uk Lee, Sung Yeon Hwang, Hee Yoon, Won Chul Cha, Tae Gun Shin, Min Seob Sim, Ik Joon Jo, Taerim Kim
Publikováno v:
Heliyon, Vol 9, Iss 8, Pp e19210- (2023)
Background and aims: This study developed a clinical support system based on federated learning to predict the need for a revised Korea Triage Acuity Scale (KTAS) to facilitate triage. Methods: This was a retrospective study that used data from 11,95
Externí odkaz:
https://doaj.org/article/f109787bf4ce49a5b2a67ff873dfeb29
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-8 (2022)
Abstract Emergency departments (EDs) are experiencing complex demands. An ED triage tool, the Score for Emergency Risk Prediction (SERP), was previously developed using an interpretable machine learning framework. It achieved a good performance in th
Externí odkaz:
https://doaj.org/article/0613b26f6d6c4e8bbb3c64518975b6f8
Autor:
Soyun Shim, Jae Yong Yu, Seyong Jekal, Yee Jun Song, Ki Tae Moon, Ju Hee Lee, Kyung Mi Yeom, Sook Hyun Park, In Sook Cho, Mi Ra Song, Sejin Heo, Jeong Hee Hong
Publikováno v:
Clinical and Experimental Emergency Medicine, Vol 9, Iss 4, Pp 345-353 (2022)
Objective Falls are one of the most frequently occurring adverse events among hospitalized patients. The Morse Fall Scale, which has been widely used for fall risk assessment, has the two limitations of low specificity and difficulty in practical imp
Externí odkaz:
https://doaj.org/article/61c1db8302d14b5e8731316566175ab9
Autor:
Junseok Jeon, Jae Yong Yu, Yeejun Song, Weon Jung, Kyungho Lee, Jung Eun Lee, Wooseong Huh, Won Chul Cha, Hye Ryoun Jang
Publikováno v:
Frontiers in Medicine, Vol 10 (2023)
IntroductionPost-donation renal outcomes are a crucial issue for living kidney donors considering young donors’ high life expectancy and elderly donors’ comorbidities that affect kidney function. We developed a prediction model for renal adaptati
Externí odkaz:
https://doaj.org/article/0d82307cea804f7baa6b29c1c48d0f74
Publikováno v:
Scientific Reports, Vol 12, Iss 1, Pp 1-10 (2022)
Abstract Providing timely intervention to critically ill patients is a challenging task in emergency departments (ED). Our study aimed to predict early critical interventions (CrIs), which can be used as clinical recommendations. This retrospective o
Externí odkaz:
https://doaj.org/article/bdca65dd8fe54d9aa55d6ce55ba70477