Bladder Cancer and Artificial Intelligence Emerging Applications

被引：7

作者：

Laurie, Mark A. ^{[1
,2
,3
,4
]}

Zhou, Steve R. ^{[1
]}

Islam, Md Tauhidul ^{[2
]}

Shkolyar, Eugene ^{[1
,3
]}

Xing, Lei ^{[2
]}

Liao, Joseph C. ^{[1
,3
,5
]}

机构：

[1] Stanford Univ, Dept Urol, Sch Med, 453 Quarry Rd,Mail Code 5656, Palo Alto, CA 94304 USA

[2] Stanford Univ, Dept Radiat Oncol, Sch Med, 875 Blake Wilbur Dr Room G204, Stanford, CA 94305 USA

[3] Vet Affairs Palo Alto Hlth Care Syst, Palo Alto, CA 94304 USA

[4] Stanford Univ, Inst Computat & Math Engn, Sch Engn, Stanford, CA 94305 USA

[5] 453 Quarry Rd,Mail Code 5656, Palo Alto, CA 94304 USA

来源：

UROLOGIC CLINICS OF NORTH AMERICA | 2024年 / 51卷 / 01期

关键词：

Artificial intelligence; Urology; Bladder cancer; Deep learning; AI-assisted diagnosis; Image processing; Treatment planning; Outcome prediction; RADICAL CYSTECTOMY; UROTHELIAL CARCINOMA; NEURAL-NETWORK; PREDICTION; RECURRENCE; DIAGNOSIS; ACCURACY; TUMOR; RISK; RADIOTHERAPY;

D O I：

10.1016/j.ucl.2023.07.002

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：

[No abstract available]

引用

页码：63 / 75

页数：13

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