Zobrazeno 1 - 10 of 20 pro vyhledávání: '"Chun-Chuan Hsu"'
1
Akademický článek
Machine learning models for predicting unscheduled return visits to an emergency department: a scoping review
Autor: Yi-Chih Lee, Chip-Jin Ng, Chun-Chuan Hsu, Chien-Wei Cheng, Shou-Yen Chen
Publikováno v: BMC Emergency Medicine, Vol 24, Iss 1, Pp 1-10 (2024)
Abstract Background Unscheduled return visits (URVs) to emergency departments (EDs) are used to assess the quality of care in EDs. Machine learning (ML) models can incorporate a wide range of complex predictors to identify high-risk patients and redu
Externí odkaz: https://doaj.org/article/c6d93e6688c3465d8b301f82245a39ff
Zobrazit plný text záznamu
2
Akademický článek
Machine Learning Models for Predicting Mortality in Patients with Cirrhosis and Acute Upper Gastrointestinal Bleeding at an Emergency Department: A Retrospective Cohort Study
Autor: Shih-Chien Tsai, Ching-Heng Lin, Cheng-C. J. Chu, Hsiang-Yun Lo, Chip-Jin Ng, Chun-Chuan Hsu, Shou-Yen Chen
Publikováno v: Diagnostics, Vol 14, Iss 17, p 1919 (2024)
Background: Cirrhosis is a major global cause of mortality, and upper gastrointestinal (GI) bleeding significantly increases the mortality risk in these patients. Although scoring systems such as the Child–Pugh score and the Model for End-stage Liv
Externí odkaz: https://doaj.org/article/19840a60dfdc4219b34e688a9474dc21
Zobrazit plný text záznamu
3
Akademický článek
A Machine Learning Model for Predicting Unscheduled 72 h Return Visits to the Emergency Department by Patients with Abdominal Pain
Autor: Chun-Chuan Hsu, Cheng-C.J. Chu, Ching-Heng Lin, Chien-Hsiung Huang, Chip-Jin Ng, Guan-Yu Lin, Meng-Jiun Chiou, Hsiang-Yun Lo, Shou-Yen Chen
Publikováno v: Diagnostics, Vol 12, Iss 1, p 82 (2021)
Seventy-two-hour unscheduled return visits (URVs) by emergency department patients are a key clinical index for evaluating the quality of care in emergency departments (EDs). This study aimed to develop a machine learning model to predict 72 h URVs f
Externí odkaz: https://doaj.org/article/83f88c107f9e4cc484d25e9e59e889c1
Zobrazit plný text záznamu
4
Dissertation/ Thesis
The spontaneous magnetism of bismuth nanoparticles by interparticle interaction
Autor: Chun-Chuan Hsu, 許均銓
97
Two sets of nano-sized bismuth powder samples were fabricated by the thermal evaporation method. The atomic force microscope image, x-ray diffraction patterns, and x-ray fluorescence pattern were used to determine the particle size and compos
Externí odkaz: http://ndltd.ncl.edu.tw/handle/3rw38p
Zobrazit plný text záznamu
6
A Machine Learning Model for Predicting Unscheduled 72 h Return Visits to the Emergency Department by Patients with Abdominal Pain
Autor: Chun-Chuan Hsu, Cheng-C.J. Chu, Ching-Heng Lin, Chien-Hsiung Huang, Chip-Jin Ng, Guan-Yu Lin, Meng-Jiun Chiou, Hsiang-Yun Lo, Shou-Yen Chen
Publikováno v: Diagnostics, Vol 12, Iss 82, p 82 (2022)
Diagnostics; Volume 12; Issue 1; Pages: 82
Diagnostics
Seventy-two-hour unscheduled return visits (URVs) by emergency department patients are a key clinical index for evaluating the quality of care in emergency departments (EDs). This study aimed to develop a machine learning model to predict 72 h URVs f
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d7801bae6c7247f0c567df3f0f1ab15
https://www.mdpi.com/2075-4418/12/1/82
Zobrazit plný text záznamu
7
In Situ Co–O Bond Reinforcement of the Artificial Cathode Electrolyte Interphase in Highly Delithiated LiCoO2 for High-Energy-Density Applications
Autor: Chi-Liang Chen, Chun-Chuan Hsu, Chusnul Khotimah, Fu-Ming Wang, Yi-Shiuan Wu, Endazenaw Bizuneh Chemere, Kefyalew Wagari Guji, Nan-Hung Yeh, Wen-Chen Chien, Laurien Merinda
Publikováno v: ACS Applied Materials & Interfaces. 13:46703-46716
Highly delithiated LiCoO2 has high specific capacity (>200 mAh g-1); however, its degradation behavior causes it to have poor electrochemical performance and thermal instability. The degradation of highly delithiated LiCoO2 is mainly induced by oxyge
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5121e954de68d2ec05493a76f5db7fd7
https://doi.org/10.1021/acsami.1c13523
Zobrazit plný text záznamu
8
Effective Ru/CNT Cathode for Rechargeable Solid-State Li–CO2 Batteries
Autor: Zizheng Tong, Ru-Shi Liu, Da-Hua Wei, Kevin Iputera, Chien Hung Chen, You Ruei Chen, Fu-Ming Wang, Shu Fen Hu, Chun Chuan Hsu, Kirankumar Venkatesan Savunthari
Publikováno v: ACS Applied Materials & Interfaces. 13:44266-44273
An effective Ru/CNT electrocatalyst plays a crucial role in solid-state lithium-carbon dioxide batteries. In the present article, ruthenium metal decorated on a multi-walled carbon nanotubes (CNTs) is introduced as a cathode for the lithium-carbon di
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::5c469738767a116758356f7618eef399
https://doi.org/10.1021/acsami.1c11000
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje