Standardized Reporting of Machine Learning Applications in Urology: The STREAM-URO Framework

被引：34
|
作者：
Kwong, Jethro C. C. [1 ,2 ]
McLoughlin, Louise C. [1 ,2 ]
Haider, Masoom [3 ,4 ]
Goldenberg, Mitchell G. [1 ]
Erdman, Lauren [5 ,6 ]
Rickard, Mandy [7 ]
Lorenzo, Armando J. [1 ,7 ]
Hung, Andrew J. [8 ]
Farcas, Monica [1 ]
Goldenberg, Larry [9 ]
Nguan, Chris [9 ]
Braga, Luis H. [10 ]
Mamdani, Muhammad [2 ,6 ,11 ]
Goldenberg, Anna [2 ,5 ,6 ]
Kulkarni, Girish S. [1 ,2 ]
机构：
[1] Univ Toronto, Dept Surg, Div Urol, Toronto, ON, Canada
[2] Univ Toronto, Temerty Ctr AI Res & Educ Med, Toronto, ON, Canada
[3] Univ Toronto, Joint Dept Med Imaging, Toronto, ON, Canada
[4] Sinai Hlth Syst, Radi & Oncol Imaging Res Lab, AI, Lunenfeld Tanenbaum Res Inst, Toronto, ON, Canada
[5] Univ Toronto, Dept Comp Sci, Toronto, ON, Canada
[6] Vector Inst, Toronto, ON, Canada
[7] Hosp Sick Children, Div Urol, Toronto, ON, Canada
[8] Univ Southern Calif, Ctr Robot Simulat & Educ, Catherine & Joseph Aresty Dept Urol, Inst Urol, Los Angeles, CA USA
[9] Univ British Columbia, Dept Urol Sci, Vancouver, BC, Canada
[10] McMaster Univ, Div Urol, Dept Surg, Toronto, ON, Canada
[11] Unity Hlth Toronto, Toronto, ON, Canada
来源：
EUROPEAN UROLOGY FOCUS | 2021年 / 7卷 / 04期
关键词：
ARTIFICIAL-INTELLIGENCE; HEALTH;
D O I：
10.1016/j.euf.2021.07.004
中图分类号：
R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];
学科分类号：
1002 ; 100201 ;
摘要：
引用
收藏
页码：672 / 682
页数：11
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