Zobrazeno 1 - 10
of 45
pro vyhledávání: '"Cheng Sheng Yu"'
Autor:
Kuan-Lin Chiu, Yu-Da Chen, Sen-Te Wang, Tzu-Hao Chang, Jenny L Wu, Chun-Ming Shih, Cheng-Sheng Yu
Publikováno v:
Metabolites, Vol 13, Iss 7, p 822 (2023)
Metabolic syndrome (MetS) includes several conditions that can increase an individual’s predisposition to high-risk cardiovascular events, morbidity, and mortality. Non-alcoholic fatty liver disease (NAFLD) is a predominant cause of cirrhosis, whic
Externí odkaz:
https://doaj.org/article/6fd369954bf44de9b0ee24f5b5bd4733
Autor:
Lin, Kai-Chun, Hsieh, Cheng-Ta, Chen, Shiu-Jau, Tsai, Cheng-Chia, Cheng, Sheng-Yu, Lin, Jui-Feng, Yang, Chih-Chuan, Hu, Chao-Kai, Chan, Yun-Kai, Lin, Hsin-Yao
Publikováno v:
Formosan Journal of Surgery; Sep/Oct2024, Vol. 57 Issue 5, p189-194, 6p
Autor:
Cheng-Sheng Yu, Shy-Shin Chang, Tzu-Hao Chang, Jenny L Wu, Yu-Jiun Lin, Hsiung-Fei Chien, Ray-Jade Chen
Publikováno v:
Journal of Medical Internet Research, Vol 23, Iss 7, p e31085 (2021)
Externí odkaz:
https://doaj.org/article/d0b579373f3b43298e1b4e16c918a1f5
Publikováno v:
Frontiers in Medicine, Vol 8 (2021)
Introduction: A third of the world's population is classified as having Metabolic Syndrome (MetS). Traditional diagnostic criteria for MetS are based on three or more of five components. However, the outcomes of patients with different combinations o
Externí odkaz:
https://doaj.org/article/be40b2d0f76a4998bb6dda8a5858473c
Autor:
Yang, Chih-Chuan, Tsai, Cheng-Chia, Chen, Shiu-Jau, Chiang, Ming-Fu, Lin, Jui-Feng, Hu, Chao-Kai, Chan, Yun-kai, Lin, Hsin-Yao, Cheng, Sheng-Yu
Publikováno v:
In International Journal of Gerontology March 2018 12(1):57-61
Chronic Subdural Hematoma in Elderly Taiwan Patients: A Retrospective Analysis of 342 Surgical Cases
Publikováno v:
In International Journal of Gerontology March 2014 8(1):37-41
Publikováno v:
European Journal of Gastroenterology & Hepatology. 33:1117-1123
OBJECTIVE End-stage liver disease is a global public health problem with a high mortality rate. Early identification of people at risk of poor prognosis is fundamental for decision-making in clinical settings. This study created a machine learning pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ea1fe19bbb4cc2eb37a6f658237c9319
https://doi.org/10.1097/meg.0000000000002169
https://doi.org/10.1097/meg.0000000000002169
Autor:
Cheng-Sheng Yu, Shy-Shin Chang, Tzu-Hao Chang, Jenny L Wu, Yu-Jiun Lin, Hsiung-Fei Chien, Ray-Jade Chen
UNSTRUCTURED This is a correction for the published manuscript: A COVID-19 Pandemic Artificial Intelligence-Based System With Deep Learning Forecasting and Automatic Statistical Data Acquisition: Development and Implementation Study (J Med Internet R
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c4836773353d781c459d15029a2affed
https://doi.org/10.2196/preprints.31085
https://doi.org/10.2196/preprints.31085
Autor:
Cheng-Sheng Yu, Shy-Shin Chang, Tzu-Hao Chang, Jenny L Wu, Yu-Jiun Lin, Hsiung-Fei Chien, Ray-Jade Chen
BACKGROUND More than 79.2 million confirmed COVID-19 cases and 1.7 million deaths were caused by SARS-CoV-2; the disease was named COVID-19 by the World Health Organization. Control of the COVID-19 epidemic has become a crucial issue around the globe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31a555056ce364a7caa326c4243df5e1
https://doi.org/10.2196/preprints.27806
https://doi.org/10.2196/preprints.27806
Autor:
Li Chuan Chen, Cheng Sheng Yu, Shy Shin Chang, Jui Hsiang Tang, Yu Jiun Lin, Jenny L. Wu, Ray Jade Chen
Publikováno v:
JMIR Medical Informatics, Vol 8, Iss 10, p e24305 (2020)
JMIR Medical Informatics
JMIR Medical Informatics
Background Patients with end-stage liver disease (ESLD) have limited treatment options and have a deteriorated quality of life with an uncertain prognosis. Early identification of ESLD patients with a poor prognosis is valuable, especially for pallia
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cbbe099d6bf9f2970e465a694631f9e8
http://medinform.jmir.org/2020/10/e24305/
http://medinform.jmir.org/2020/10/e24305/