2022
DOI: 10.21203/rs.3.rs-1570686/v1
|View full text |Cite
Preprint
|
Sign up to set email alerts
|

A Deep Learning Approach for Predicting Clinically Significant Prostate Cancer: A Retrospective, Multicentre Study

Abstract: Purpose: To construct deep learning (DL) models based on multicentre biparametric MRI (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa), and compare the performance of these models with that of Prostate Imaging Reporting and Data System (PI-RADS) assessment of expert-level radiologists based on multiparametric MRI (mpMRI).Methods: This study included 1861 consecutive men with mpMRI from seven hospitals, who underwent radical prostatectomy or biopsy. These patients were divided into tr… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

0
0
0

Publication Types

Select...

Relationship

0
0

Authors

Journals

citations
Cited by 0 publications
references
References 22 publications
0
0
0
Order By: Relevance

No citations

Set email alert for when this publication receives citations?