Integration of clinicopathologic identification and deep transferrable image feature representation improves predictions of lymph node metastasis in prostate cancer

Integration of clinicopathologic identification and deep transferrable image feature representation improves predictions of lymph node metastasis in prostate cancer

Background: Accurate identification of pelvic lymph node metastasis (PLNM) in patients with prostate cancer (PCa) is crucial for determining appropriate treatment options. Here, we built a PLNM-Risk calculator to obtain a precisely informed decision about whether to perform extended pelvic lymph nod...

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Bibliographic Details
Main Authors: Ying Hou, Jie Bao, Yang Song, Mei-Ling Bao, Ke-Wen Jiang, Jing Zhang, Guang Yang, Chun-Hong Hu, Hai-Bin Shi, Xi-Ming Wang, Yu-Dong Zhang
Format: Article
Language:English
Published: Elsevier 2021-06-01
Series:EBioMedicine
Subjects:
Pelvic lymph node metastasis
Prostate cancer
Radiomics
Deep learning
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396421001882

Internet

http://www.sciencedirect.com/science/article/pii/S2352396421001882

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