文献
J-GLOBAL ID:202202275138716841
整理番号:22A0983231
救急科患者の潜在サブグループの遡及的同定:機械学習アプローチ【JST・京大機械翻訳】
Retrospective identification of latent subgroups of emergency department patients: A machine learning approach
著者 (11件):
Duwalage Kalpani I
(School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia)
,
Duwalage Kalpani I
(Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia)
,
Duwalage Kalpani I
(ARC Centre of Excellence for Mathematical and Statistical Frontiers, Melbourne, Victoria, Australia)
,
Burkett Ellen
(Emergency Department, Princess Alexandra Hospital, Brisbane, Queensland, Australia)
,
Burkett Ellen
(Queensland Government Clinical Excellence Division, Healthcare Improvement Unit, Brisbane, Queensland, Australia)
,
White Gentry
(School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia)
,
White Gentry
(Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia)
,
White Gentry
(ARC Centre of Excellence for Mathematical and Statistical Frontiers, Melbourne, Victoria, Australia)
,
Wong Andy
(Emergency Department, Princess Alexandra Hospital, Brisbane, Queensland, Australia)
,
Thompson M Helen
(School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia)
,
Thompson M Helen
(Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia)
資料名:
Emergency Medicine Australasia
(Emergency Medicine Australasia)
巻:
34
号:
2
ページ:
252-262
発行年:
2022年
JST資料番号:
W2557A
ISSN:
1742-6731
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
アメリカ合衆国 (USA)
言語:
英語 (EN)