Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Fan-Ya Chou"'
Autor:
Joyce Tay, Yi-Hsuan Yen, Kevin Rivera, Eric H Chou, Chih-Hung Wang, Fan-Ya Chou, Jen-Tang Sun, Shih-Tsung Han, Tzu-Ping Tsai, Yen-Chia Chen, Toral Bhakta, Chu-Lin Tsai, Tsung-Chien Lu, Matthew Huei-Ming Ma
Publikováno v:
Western Journal of Emergency Medicine, Vol 25, Iss 1, Pp 67-78 (2023)
Introduction: Timely diagnosis of patients affected by an emerging infectious disease plays a crucial role in treating patients and avoiding disease spread. In prior research, we developed an approach by using machine learning (ML) algorithms to pred
Externí odkaz:
https://doaj.org/article/c6804f84ab914c5c914f5bb4722b0cf8
Autor:
Fan-Ya Chou, Te-Fa Chiu, Fen-Wei Huang, Tai-Yi Hsu, Chien-Yu Liu, Chin-Han Lin, Po-Yao Huang, Kuei-Ming Lin, Shih-Hao Wu
Publikováno v:
Frontiers in Cardiovascular Medicine, Vol 10 (2023)
IntroductionSleep disturbance and insufficient sleep have been linked to metabolic syndrome, increasing cardiovascular disease and mortality risk. However, few studies investigate the joint effect of sleep and exercise on metabolic syndrome. We hypot
Externí odkaz:
https://doaj.org/article/bd273c20f1354ceca3b8c1a8f57875d8
Autor:
Sot Shih-Hung Liu, Cheng-Jiun Ma, Fan-Ya Chou, Michelle Yuan-Chiao Cheng, Chih-Hung Wang, Chu-Lin Tsai, Wei-Jou Duh, Chien-Hua Huang, Feipei Lai, Tsung-Chien Lu
Publikováno v:
Western Journal of Emergency Medicine, Vol 24, Iss 4 (2023)
Introduction: Healthcare professionals frequently experience work-related fatigue, which may jeopardize their health and put patient safety at risk. In this study, we applied a machine learning (ML) approach based on data collected from a smartwatch
Externí odkaz:
https://doaj.org/article/0815894983d44b7eb269d021b58cc835
Autor:
Tay, Joyce, Yi-Hsuan Yen, Rivera, Kevin, Chou, Eric H., Chih-Hung Wang, Fan-Ya Chou, Jen-Tang Sun, Shih-Tsung Han, Tzu-Ping Tsai, Yen-Chia Chen, Bhakta, Toral, Chu-Lin Tsai, Tsung-Chien Lu, Huei-Ming Ma, Matthew
Publikováno v:
Western Journal of Emergency Medicine: Integrating Emergency Care with Population Health; Jan2024, Vol. 25 Issue 1, p67-78, 12p
Autor:
Chu-Lin Tsai, Eric H Chou, Robert Risch, Matthew Huei-Ming Ma, Toral Bhakta, Tsung-Chien Lu, John S. Garrett, Fan-Ya Chou, Jon Wolfshohl, Dahlia Hassani, Gerald O. Ogola, Andrew Shedd, James P d'Etienne, Chih-Hung Wang
Publikováno v:
Internal and Emergency Medicine
There are only a few models developed for risk-stratifying COVID-19 patients with suspected pneumonia in the emergency department (ED). We aimed to develop and validate a model, the COVID-19 ED pneumonia mortality index (CoV-ED-PMI), for predicting m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5101426a8a35599b77fd2a0a9523b653
https://doi.org/10.1007/s11739-021-02882-x
https://doi.org/10.1007/s11739-021-02882-x
Autor:
Tsung-Chien Lu, Chih-Hung Wang, Fan-Ya Chou, Jen-Tang Sun, Eric H. Chou, Edward Pei-Chuan Huang, Chu-Lin Tsai, Matthew Huei-Ming Ma, Cheng-Chung Fang, Chien-Hua Huang
Publikováno v:
Internal and emergency medicine.
In-hospital cardiac arrest (IHCA) in the emergency department (ED) is not uncommon but often fatal. Using the machine learning (ML) approach, we sought to predict ED-based IHCA (EDCA) in patients presenting to the ED based on triage data. We retrieve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::21f4fdb1510dbfb1d04c768b01d6268f
https://pubmed.ncbi.nlm.nih.gov/36335518
https://pubmed.ncbi.nlm.nih.gov/36335518
Autor:
Sot Shih-Hung Liu, Cheng-Jiun Ma, Fan-Ya Chou, Michelle Yuan-Chiao Cheng, Wei-Jou Duh, Chien-Hua Huang, Feipei Lai, Tsung-Chien Lu
BACKGROUND Work-related fatigue has been a common problem in the workplaces. The healthcare providers are particularly prone to work-related fatigue, which may jeopardize their own health and put patient safety at risk. Past studies often conducted i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::30c0355701e937a4c996a9d8eecd2c8d
https://doi.org/10.2196/preprints.36073
https://doi.org/10.2196/preprints.36073
