Comparison of machine learning methods to predict urinary incontinence in localized prostate cancer

被引：0

作者：

Hasannejadasl, H. ^{[1
]}

van de Poel, H. ^{[2
]}

Vanneste, B. ^{[3
]}

van Roermund, J. ^{[4
]}

Aben, K. ^{[5
,6
]}

Zheng, Z. ^{[1
]}

Osong, B. ^{[1
]}

Kiemeney, L. ^{[5
]}

Van Oort, I. ^{[7
]}

Verwey, R. ^{[8
]}

Hochstenbach, L. ^{[8
]}

Bloemen, E. ^{[8
]}

Dekker, A. ^{[1
]}

Fijten, R. ^{[1
]}

机构：

[1] Maastricht Univ, Dept Radiat Oncol Maastro, Med Ctr, Maastricht, Netherlands

[2] Univ Amsterdam, Dept Urol, Med Ctr, Amsterdam, Netherlands

[3] Maastricht Univ, Dept Radiat Oncol Maastro, Med Ctr, Maastricht, Netherlands

[4] Maastricht Univ, Dept Urol, Med Ctr, Maastricht, Netherlands

[5] Netherlands Comprehens Canc Org, Dept Res & Dev, Utrecht, Netherlands

[6] Radboud Univ Nijmegen, Radboud Inst Hlth Sci, Med Ctr, Nijmegen, Netherlands

[7] Radboud Univ Nijmegen, Dept Urol, Med Ctr, Nijmegen, Netherlands

[8] Zuyd Univ, Dept Appl Sci, Heerlen, Netherlands

来源：

RADIOTHERAPY AND ONCOLOGY | 2023年 / 182卷

关键词：

D O I：

暂无

中图分类号：

R73 [肿瘤学];

学科分类号：

100214 ;

摘要：

PO-1523

引用

页码：S1238 / S1239

页数：2

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