Convolutional neural networks for prostate cancer detection, classification, and segmentation: A systematic review and bibliometric analysis

CNN-based prostate cancer detection, classification, and segmentation demonstrate promise for improving diagnostic accuracy and clinical workflow efficiency, though challenges in dataset standardization, regulatory compliance, and clinical integration remain to be addressed.

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Publication Details

Journal
European Journal of Radiology Open
Published
2026-03-03
DOI
https://doi.org/10.1016/j.ejro.2026.100741
Primary Topic
AI in cancer detection
Type
article
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article

Convolutional neural networks for prostate cancer detection, classification, and segmentation: A systematic review and bibliometric analysis

Burak Gülmez
European Journal of Radiology Open
AI in cancer detection
article

Convolutional neural networks for prostate cancer detection, classification, and segmentation: A systematic review and bibliometric analysis

Burak Gülmez
article en

Abstract

CNN-based prostate cancer detection, classification, and segmentation demonstrate promise for improving diagnostic accuracy and clinical workflow efficiency, though challenges in dataset standardization, regulatory compliance, and clinical integration remain to be addressed.

European Journal of Radiology OpenVol. 16
University College Dublin (IE), Kütahya Dumlupınar Üniversitesi (TR)
Good health and well-being
Openalex Percentile: Top 40%
AI in cancer detection
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Convolutional neural networks for prostate cancer detection, classification, and segmentation: A systematic review and bibliometric analysis — Burak Gülmez · European Journal of Radiology Open (2026) | TGRS Research Map | TGRS