文献
J-GLOBAL ID:202202265349635022
整理番号:22A0506245
機械学習由来最適分類木を用いた先天性心疾患のベンチマーキング【JST・京大機械翻訳】
Benchmarking in Congenital Heart Surgery Using Machine Learning-Derived Optimal Classification Trees
著者 (11件):
Bertsimas Dimitris
(Operations Research Center and Sloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA)
,
Zhuo Daisy
(Alexandria Health, Cambridge, MA, USA)
,
Zhuo Daisy
(Alexandria Health, Providence, RI, USA)
,
Levine Jordan
(Alexandria Health, Cambridge, MA, USA)
,
Levine Jordan
(Alexandria Health, Providence, RI, USA)
,
Dunn Jack
(Alexandria Health, Cambridge, MA, USA)
,
Dunn Jack
(Alexandria Health, Providence, RI, USA)
,
Tobota Zdzislaw
( Children’s Memorial Health Institute, Warsaw, Poland)
,
Maruszewski Bohdan
( Children’s Memorial Health Institute, Warsaw, Poland)
,
Fragata Jose
(Hospital de Santa Marta and NOVA University, Lisbon, Portugal)
,
Sarris George E
(Athens Heart Surgery Institute, Athens, Greece)
資料名:
World Journal for Pediatric and Congenital Heart Surgery
(World Journal for Pediatric and Congenital Heart Surgery)
巻:
13
号:
1
ページ:
23-35
発行年:
2022年
JST資料番号:
W5434A
ISSN:
2150-1351
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)