Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Chih-Chi Su"'
Autor:
Shin-Fu Chen, Chih-Chi Su, Chuan-Ching Huang, Paul T. Ogink, Hung-Kuan Yen, Olivier Q. Groot, Ming-Hsiao Hu
Publikováno v:
Journal of the Formosan Medical Association, Vol 122, Iss 12, Pp 1321-1330 (2023)
Background/Purpose: Identifying patients at risk of prolonged opioid use after surgery prompts appropriate prescription and personalized treatment plans. The Skeletal Oncology Research Group machine learning algorithm (SORG-MLA) was developed to pred
Externí odkaz:
https://doaj.org/article/cb8263ab01964a81b313766a380bfcc8
Autor:
Cheng-Chen Tsai, Chuan-Ching Huang, Ching-Wei Lin, Paul T. Ogink, Chih-Chi Su, Shin-Fu Chen, Mao-Hsu Yen, Jorrit-Jan Verlaan, Joseph H. Schwab, Chen-Ti Wang, Olivier Q. Groot, Ming-Hsiao Hu, Hongsen Chiang
Publikováno v:
BMC Musculoskeletal Disorders, Vol 24, Iss 1, Pp 1-11 (2023)
Abstract Background Preoperative prediction of prolonged postoperative opioid use (PPOU) after total knee arthroplasty (TKA) could identify high-risk patients for increased surveillance. The Skeletal Oncology Research Group machine learning algorithm
Externí odkaz:
https://doaj.org/article/ebeb7395cdf343da967a040bc357ed6a
Autor:
Chih-Chi Su, Yen-Po Lin, Hung-Kuan Yen, Yu-Ting Pan, Hester Zijlstra, Jorrit-Jan Verlaan, Joseph H. Schwab, Cheng-Yo Lai, Ming-Hsiao Hu, Shu-Hua Yang, Olivier Q. Groot
Publikováno v:
Journal of the American Academy of Orthopaedic Surgeons.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9b3c76597c0c6998d520e31b68375e6e
https://doi.org/10.5435/jaaos-d-23-00091
https://doi.org/10.5435/jaaos-d-23-00091
Autor:
Hung-Kuan Yen, Paul T. Ogink, Chuan-Ching Huang, Olivier Q. Groot, Chih-Chi Su, Shin-Fu Chen, Chih-Wei Chen, Aditya V. Karhade, Kuang-Ping Peng, Wei-Hsin Lin, HongSen Chiang, Jiun-Jen Yang, Shih-Hsiang Dai, Mao-Hsu Yen, Jorrit-Jan Verlaan, Joseph H. Schwab, Tze-Hong Wong, Shu-Hua Yang, Ming-Hsiao Hu
Publikováno v:
The Spine Journal. 22:1119-1130
Preoperative prediction of prolonged postoperative opioid prescription helps identify patients for increased surveillance after surgery. The SORG machine learning model has been developed and successfully tested using 5,413 patients from the United S
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7e6490fb6c982ffe051a7a5e975542b5
https://doi.org/10.1016/j.spinee.2022.02.009
https://doi.org/10.1016/j.spinee.2022.02.009
