Letter to the Editor on “Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review”

被引：0

作者：

Alessandro Bevilacqua

Margherita Mottola

机构：

[1] University of Bologna,Department of Computer Science and Engineering (DISI)

[2] University of Bologna,Advanced Research Center On Electronics Systems (ARCES)

[3] University of Bologna,Department of Medical and Surgical Sciences (DIMEC)

来源：

Insights into Imaging | / 14卷

关键词：

Artificial intelligence; Machine learning; Prostate cancer;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

共 6 条

[1]

Sushentsev N(2022)Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review Insights Imaging 13 1-17

[2]

Moreira Da Silvia N(2021)The primacy of high B-Value 3T-DWI radiomics in the prediction of clinically significant prostate cancer Diagnostics (Basel) 11 739-undefined

[3]

Yeung M(undefined)undefined undefined undefined undefined-undefined

[4]

Bevilacqua A(undefined)undefined undefined undefined undefined-undefined

[5]

Mottola M(undefined)undefined undefined undefined undefined-undefined

[6]

Ferroni F(undefined)undefined undefined undefined undefined-undefined

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