文献
J-GLOBAL ID:202002274642140790
整理番号:20A0066957
患者の無症状を予測するための位置ベース学習と自己適応型コホート知能に基づく新しい特徴選択法【JST・京大機械翻訳】
New feature selection methods based on opposition-based learning and self-adaptive cohort intelligence for predicting patient no-shows
著者 (5件):
Aladeemy Mohammed
(Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Binghamton, NY 13902, USA)
,
Adwan Linda
(Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Binghamton, NY 13902, USA)
,
Booth Amy
(United Health Services Hospitals, Binghamton, NY 13903, USA)
,
Khasawneh Mohammad T.
(Department of Systems Science and Industrial Engineering, State University of New York at Binghamton, Binghamton, NY 13902, USA)
,
Poranki Srikanth
(United Health Services Hospitals, Binghamton, NY 13903, USA)
資料名:
Applied Soft Computing
(Applied Soft Computing)
巻:
86
ページ:
Null
発行年:
2020年
JST資料番号:
W2175A
ISSN:
1568-4946
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)