Zobrazeno 1 - 10
of 36
pro vyhledávání: '"Chien-Chin Hsu"'
Autor:
Chin-Chuan Hsu, Yuan Kao, Chien-Chin Hsu, Chia-Jung Chen, Shu-Lien Hsu, Tzu-Lan Liu, Hung-Jung Lin, Jhi-Joung Wang, Chung-Feng Liu, Chien-Cheng Huang
Publikováno v:
BMC Endocrine Disorders, Vol 23, Iss 1, Pp 1-14 (2023)
Abstract Background Hyperglycemic crises are associated with high morbidity and mortality. Previous studies have proposed methods to predict adverse outcomes of patients in hyperglycemic crises; however, artificial intelligence (AI) has never been us
Externí odkaz:
https://doaj.org/article/0fb826f1020141f48711f43a85f3758f
Autor:
Tian-Hoe Tan, Chien-Chin Hsu, Chia-Jung Chen, Shu-Lien Hsu, Tzu-Lan Liu, Hung-Jung Lin, Jhi-Joung Wang, Chung-Feng Liu, Chien-Cheng Huang
Publikováno v:
BMC Geriatrics, Vol 21, Iss 1, Pp 1-8 (2021)
Abstract Background Predicting outcomes in older patients with influenza in the emergency department (ED) by machine learning (ML) has never been implemented. Therefore, we conducted this study to clarify the clinical utility of implementing ML. Meth
Externí odkaz:
https://doaj.org/article/8ecc75e87f78427fafeac5d2fba4584d
Autor:
Pei-I Zhang, Chien-Chin Hsu, Yuan Kao, Chia-Jung Chen, Ya-Wei Kuo, Shu-Lien Hsu, Tzu-Lan Liu, Hung-Jung Lin, Jhi-Joung Wang, Chung-Feng Liu, Chien-Cheng Huang
Publikováno v:
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, Vol 28, Iss 1, Pp 1-7 (2020)
Abstract Background A big-data-driven and artificial intelligence (AI) with machine learning (ML) approach has never been integrated with the hospital information system (HIS) for predicting major adverse cardiac events (MACE) in patients with chest
Externí odkaz:
https://doaj.org/article/ef5ef2acfb9a4e96abf0ceb0686aa32d
Autor:
Wei-Chun Tsai, Chung-Feng Liu, Hung-Jung Lin, Chien-Chin Hsu, Yu-Shan Ma, Chia-Jung Chen, Chien-Cheng Huang, Chia-Chun Chen
Publikováno v:
Healthcare, Vol 10, Iss 8, p 1498 (2022)
The emergency department (ED) is at the forefront of medical care, and the medical team needs to make outright judgments and treatment decisions under time constraints. Thus, knowing how to make personalized and precise predictions is a very challeng
Externí odkaz:
https://doaj.org/article/856f46d939054495ac0ff96a6b8c3d16
Autor:
Henry Chih-Hung Tai, Chien-Chun Yeh, Yen-An Chen, Chien-Chin Hsu, Jiann-Hwa Chen, Wei-Lung Chen, Chien-Cheng Huang, Jui-Yuan Chung
Publikováno v:
BMC Infectious Diseases, Vol 19, Iss 1, Pp 1-7 (2019)
Abstract Background Systemic Inflammatory Response Syndrome (SIRS) criteria are often used to evaluate the risk of sepsis and to identify in-hospital mortality among patients with suspected infection. However, utilization of the SIRS criteria in mort
Externí odkaz:
https://doaj.org/article/c2712e3d49e1401baed7810ff15e6cb5
Autor:
Jhi-Joung Wang, Chien-Chin Hsu, Tzu-Lan Liu, You-Ming Chen, Yu-Shan Ma, Shu-Lien Hsu, Hung-Jung Lin, Chia-Jung Chen, Chien-Cheng Huang, Chung-Feng Liu, Yuan Kao, Yu-Ting Shen
Publikováno v:
Academic Emergency Medicine. 28:1277-1285
Background Artificial intelligence of things (AIoT) may be a solution for predicting adverse outcomes in emergency department (ED) patients with pneumonia; however, this issue remains unclear. Therefore, we conducted this study to clarify it. Methods
Autor:
Chia-Jung Chen, Chung-Feng Liu, Chien-Chin Hsu, Tian-Hoe Tan, Jhi-Joung Wang, Chien-Cheng Huang, Shu-Lien Hsu, Hung-Jung Lin, Tzu-Lan Liu
Publikováno v:
BMC Geriatrics
BMC Geriatrics, Vol 21, Iss 1, Pp 1-8 (2021)
BMC Geriatrics, Vol 21, Iss 1, Pp 1-8 (2021)
Background Predicting outcomes in older patients with influenza in the emergency department (ED) by machine learning (ML) has never been implemented. Therefore, we conducted this study to clarify the clinical utility of implementing ML. Methods We re
Autor:
Hsing‐Chun Hsieh, Ying‐Ling Liu, Li‐Ling Chu, Hung-Jung Lin, Chien-Chin Hsu, Kang-Ting Tsai, Pei‐Hsin Kao, Chien‐Cheng Huang, Hui‐Chen Su, Jung‐Fang Chen
Publikováno v:
Journal of the American Geriatrics Society. 67:2298-2304
OBJECTIVES Whether early medication reconciliation and integration can reduce polypharmacy and potentially inappropriate medication (PIM) in the emergency department (ED) remains unclear. Polypharmacy and PIM have been recognized as significant cause
Autor:
Chien-Chin Hsu, Jui Yuan Chung, Jiann-Hwa Chen, How Ran Guo, Hung-Jung Lin, Wei Lung Chen, Chien-Cheng Huang
Publikováno v:
The American Journal of Emergency Medicine. 37:391-394
Background The shock index is a rapid and simple tool used to predict mortality in patients with acute illnesses including sepsis, multiple trauma, and postpartum hemorrhage. However, its ability to predict mortality in geriatric patients with influe
Can the emergency department sustain the first strike? Experience from the 2016 earthquake in Tainan
Publikováno v:
Hong Kong Journal of Emergency Medicine. 26:263-267
Background: After the main shock of a major earthquake, casualties cluster in a short period and may overwhelm the capacities of health care facilities. An earthquake with a magnitude of 6.4 on the Richter scale struck Tainan City causing 117 fatalit