[HTML][HTML] A Systematic Review of the Diagnostic Accuracy of Deep Learning Models for the Automatic Detection, Localization, and Characterization of Clinically …
Background and objective Magnetic resonance imaging (MRI) plays a critical role in prostate
cancer diagnosis, but is limited by variability in interpretation and diagnostic accuracy. This …
cancer diagnosis, but is limited by variability in interpretation and diagnostic accuracy. This …
Comprehensive assessment of MRI-based artificial intelligence frameworks performance in the detection, segmentation, and classification of prostate lesions using …
Prostate cancer (PCa) detection via MRI exhibits both intrareader and interreader 1, 2
variability. The adoption of Artificial Intelligence (AI)–powered automated or semiautomated …
variability. The adoption of Artificial Intelligence (AI)–powered automated or semiautomated …
Deep Learning Based on ResNet-18 for Classification of Prostate Imaging-Reporting and Data System Category 3 Lesions
Z Kang, E **ao, Z Li, L Wang - Academic Radiology, 2024 - Elsevier
Rationale and Objectives To explore the classification and prediction efficacy of the deep
learning model for benign prostate lesions, non-clinically significant prostate cancer (non …
learning model for benign prostate lesions, non-clinically significant prostate cancer (non …
Frameworks Performance in the
LU Open-Source - Artificial Intelligence in Urology, An Issue of …, 2023 - books.google.com
Prostate cancer (PCa) detection via MRI exhibits both intrareader and interreader1, 2
variability. The adoption of Artificial Intelligence (AI)–powered automated or semiautomated …
variability. The adoption of Artificial Intelligence (AI)–powered automated or semiautomated …