Use of artificial intelligence to characterize renal tumors

Hokun Kim; Sung Hoo Hong

doi:10.4111/icu.20220051

Use of artificial intelligence to characterize renal tumors

Hokun Kim
, Sung Hoo Hong

Department of Urology

Catholic Univ. of Korea Coll. Med.

Research output: Contribution to journal › Editorial

4 Scopus citations

Original language	English
Pages (from-to)	123-125
Number of pages	3
Journal	Investigative and Clinical Urology
Volume	63
Issue number	2
DOIs	https://doi.org/10.4111/icu.20220051
State	Published - Mar 2022

Bibliographical note

Funding Information:
This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health & Welfare, Republic of Korea, Ministry of Food and Drug Safety) (Project Number: KMDF_PR_20200901_0096).

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@article{f3e711be205d436b9579f44dab3f9092,

title = "Use of artificial intelligence to characterize renal tumors",

author = "Hokun Kim and Hong, \{Sung Hoo\}",

note = "Funding Information: This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health \& Welfare, Republic of Korea, Ministry of Food and Drug Safety) (Project Number: KMDF\_PR\_20200901\_0096).",

year = "2022",

month = mar,

doi = "10.4111/icu.20220051",

language = "English",

volume = "63",

pages = "123--125",

journal = "Investigative and Clinical Urology",

issn = "2466-0493",

publisher = "Korean Urological Association",

number = "2",

}

TY - JOUR

T1 - Use of artificial intelligence to characterize renal tumors

AU - Kim, Hokun

AU - Hong, Sung Hoo

N1 - Funding Information: This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (Ministry of Science and ICT, Ministry of Trade, Industry and Energy, Ministry of Health & Welfare, Republic of Korea, Ministry of Food and Drug Safety) (Project Number: KMDF_PR_20200901_0096).

PY - 2022/3

Y1 - 2022/3

UR - https://www.scopus.com/pages/publications/85125882412

U2 - 10.4111/icu.20220051

DO - 10.4111/icu.20220051

M3 - Editorial

C2 - 35244985

AN - SCOPUS:85125882412

SN - 2466-0493

VL - 63

SP - 123

EP - 125

JO - Investigative and Clinical Urology

JF - Investigative and Clinical Urology

IS - 2

ER -

Use of artificial intelligence to characterize renal tumors

Bibliographical note

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