Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI-Reference-Cited by-同舟云学术

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Multicenter Evaluation of a Weakly Supervised Deep Learning Model for Lymph Node Diagnosis in Rectal Cancer at MRI

Published:2024-03-01 Issue:2 Volume:6 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Xia Wei^ORCID,Li Dandan,He Wenguang^ORCID,Pickhardt Perry J.^ORCID,Jian Junming^ORCID,Zhang Rui^ORCID,Zhang Junjie^ORCID,Song Ruirui^ORCID,Tong Tong^ORCID,Yang Xiaotang^ORCID,Gao Xin^ORCID,Cui Yanfen^ORCID

Funder

National Natural Science Foundation of China

China Postdoctoral Science Foundation

Outstanding Youth Foundation

Publisher

Radiological Society of North America (RSNA)

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.230152

Reference23 articles.

1. Corrections to “Rectal cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up”

2. Nomograms for Predicting Local Recurrence, Distant Metastases, and Overall Survival for Patients With Locally Advanced Rectal Cancer on the Basis of European Randomized Clinical Trials

3. For Patients with Early Rectal Cancer, Does Local Excision Have an Impact on Recurrence, Survival, and Quality of Life Relative to Radical Resection?

4. MRI of Rectal Cancer: Tumor Staging, Imaging Techniques, and Management

5. The utility of MRI for pre-operative T and N staging of gastric carcinoma: a systematic review and meta-analysis

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