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

页码：672 / 682

页数：11

共 50 条

[1] Application of STREAM-URO and APPRAISE-AI reporting standards for artificial intelligence studies in pediatric urology: A case example with pediatric hydronephrosis
Khondker, Adree
Kwong, Jethro C. C.
Rickard, Mandy
Erdman, Lauren
Kim, Jin K.
Ahmad, Ihtisham
Weaver, John
Fernandez, Nicolas
Tasian, Gregory E.
Kulkarni, Girish S.
Lorenzo, Armando J.
JOURNAL OF PEDIATRIC UROLOGY, 2024, 20 (03) : 455 - 467
[2] A Framework for Form Applications that Use Machine Learning
Aguiar, Guilherme
Vilain, Patricia
INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING - IDEAL 2018, PT I, 2018, 11314 : 773 - 782
[3] Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review
Lubbad, M.
Karaboga, D.
Basturk, A.
Akay, B.
Nalbantoglu, U.
Pacal, I.
NEURAL COMPUTING & APPLICATIONS, 2024, 36 (12): : 6355 - 6379
[4] Machine learning applications in detection and diagnosis of urology cancers: a systematic literature review
M. Lubbad
D. Karaboga
A. Basturk
B. Akay
U. Nalbantoglu
I. Pacal
Neural Computing and Applications, 2024, 36 : 6355 - 6379
[5] MLPro - An integrative middleware framework for standardized machine learning tasks in Python']Python
Arend, Detlef
Diprasetya, Mochammad Rizky
Yuwono, Steve
Schwung, Andreas
SOFTWARE IMPACTS, 2022, 14
[6] Prostate-specific Membrane Antigen Interpretation Criteria, Standardized Reporting, and the Use of Machine Learning
Seifert, Robert
Gafita, Andrei
Solnes, Lilja B.
Iagaru, Andrei
PET CLINICS, 2024, 19 (03) : 363 - 369
[7] Towards Stream-based Reasoning and Machine Learning for IoT Applications
Endler, Markus
Briot, Jean-Pierre
de Almeida, Vitor P.
Silva e Silva, Francisco
Haeusler, Edward H.
PROCEEDINGS OF THE 2017 INTELLIGENT SYSTEMS CONFERENCE (INTELLISYS), 2017, : 202 - 209
[8] A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology
Hesham Salem
Daniele Soria
Jonathan N. Lund
Amir Awwad
BMC Medical Informatics and Decision Making, 21
[9] A systematic review of the applications of Expert Systems (ES) and machine learning (ML) in clinical urology
Salem, Hesham
Soria, Daniele
Lund, Jonathan N.
Awwad, Amir
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2021, 21 (01)
[10] Feature Engineering and Machine Learning Framework for DDoS Attack Detection in the Standardized Internet of Things
Kamaldeep, Manisha
Malik, Manisha
Dutta, Maitreyee
IEEE INTERNET OF THINGS JOURNAL, 2023, 10 (10) : 8658 - 8669

← 1 2 3 4 5 →