Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer-Reference-Cited by-同舟云学术

Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer

Published:2021-05-05 Issue:3 Volume:128 Page:352-360
ISSN:1464-4096
Container-title:BJU International
language:en
Short-container-title:BJU Int

Author:

Wessels Frederik¹²^ORCID,Schmitt Max¹,Krieghoff‐Henning Eva¹,Jutzi Tanja¹,Worst Thomas S.²,Waldbillig Frank²,Neuberger Manuel²,Maron Roman C.¹,Steeg Matthias³,Gaiser Timo³,Hekler Achim¹,Utikal Jochen S.⁴⁵,Kalle Christof⁶,Fröhling Stefan⁷,Michel Maurice S.²,Nuhn Philipp²,Brinker Titus J.¹^ORCID

Affiliation:

1. Digital Biomarkers for Oncology Group National Center for Tumor Diseases (NCT) German Cancer Research Center (DKFZ) HeidelbergGermany

2. Department of Urology and Urological Surgery Medical Faculty Mannheim of Heidelberg University University Medical Center Mannheim MannheimGermany

3. Institute of Pathology Medical Faculty Mannheim of Heidelberg University University Medical Center Mannheim MannheimGermany

4. Skin Cancer Unit German Cancer Research Center (DKFZ) HeidelbergGermany

5. Department of Dermatology, Venereology and Allergology University Medical Center Mannheim University of Heidelberg HeidelbergGermany

6. Department of Clinical‐Translational Sciences Berlin Institute of Health (BIH) Charité University Medicine BerlinGermany

7. National Center for Tumor Diseases German Cancer Research Center Heidelberg Germany

Funder

Bundesministerium für Gesundheit

Publisher

Wiley

Subject

Urology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/bju.15386

Reference37 articles.

1. Cancer incidence and mortality patterns in Europe: Estimates for 40 countries and 25 major cancers in 2018

2. Two Positive Nodes Represent a Significant Cut-off Value for Cancer Specific Survival in Patients with Node Positive Prostate Cancer. A New Proposal Based on a Two-Institution Experience on 703 Consecutive N+ Patients Treated with Radical Prostatectomy, Extended Pelvic Lymph Node Dissection and Adjuvant Therapy

3. EAU Guidelines.Edn. presented at the EAU Annual Congress Amsterdam 2020. ISBN 978‐94‐92671‐07‐3

4. A Novel Nomogram to Identify Candidates for Extended Pelvic Lymph Node Dissection Among Patients with Clinically Localized Prostate Cancer Diagnosed with Magnetic Resonance Imaging-targeted and Systematic Biopsies

5. Updated Nomogram Predicting Lymph Node Invasion in Patients with Prostate Cancer Undergoing Extended Pelvic Lymph Node Dissection: The Essential Importance of Percentage of Positive Cores

Cited by 44 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Correlation between 18F-FDG PET/CT metabolic parameters and microvascular invasion before liver transplantation in patients with hepatocellular carcinoma;Nuclear Medicine Communications;2024-09-13

2. Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images;Journal of Translational Medicine;2024-06-14

3. MAMILNet: advancing precision oncology with multi-scale attentional multi-instance learning for whole slide image analysis;Frontiers in Oncology;2024-04-30

4. Harnessing artificial intelligence for prostate cancer management;Cell Reports Medicine;2024-04

5. Deep learning-based radiomics model from pretreatment ADC to predict biochemical recurrence in advanced prostate cancer;Frontiers in Oncology;2024-02-27