<p>Pancreatic Ductal Adenocarcinoma: Machine Learning–Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade</p>-Reference-Cited by-同舟云学术

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Pancreatic Ductal Adenocarcinoma: Machine Learning–Based Quantitative Computed Tomography Texture Analysis For Prediction Of Histopathological Grade

Published:2019-10 Issue: Volume:Volume 11 Page:9253-9264
ISSN:1179-1322
Container-title:Cancer Management and Research
language:en
Short-container-title:CMAR

Author:

Qiu Wenli,Duan Na,Chen Xiao,Ren Shuai,Zhang Yifen,Wang Zhongqiu,Chen Rong

Publisher

Informa UK Limited

Subject

Oncology

Cited by 30 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. Comparative analysis of machine learning and deep learning models for improved cancer detection: A comprehensive review of recent advancements in diagnostic techniques;Expert Systems with Applications;2024-12

2. Pancreatic Ductal Adenocarcinoma (PDAC): A Review of Recent Advancements Enabled by Artificial Intelligence;Cancers;2024-06-17

3. Pancreatic mucinous adenocarcinoma has different clinical characteristics and better prognosis compared to non-specific PDAC: A retrospective observational study;Heliyon;2024-05

4. Computed tomography-based radiomics diagnostic approach for differential diagnosis between early- and late-stage pancreatic ductal adenocarcinoma;World Journal of Gastrointestinal Oncology;2024-04-15

5. Dual-layer spectral detector CT: A noninvasive preoperative tool for predicting histopathological differentiation in pancreatic ductal adenocarcinoma;European Journal of Radiology;2024-04

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