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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A multimodal model fusing multiphase contrast-enhanced CT and clinical characteristics for predicting lymph node metastases of pancreatic cancer
Qian Lu, Chenjie Zhou, Haojie Zhang, et al.
Physics in Medicine and Biology (2022) Vol. 67, Iss. 17, pp. 175002-175002
Closed Access | Times Cited: 9

Showing 9 citing articles:

A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study
Ningzhen Fu, Wenli Fu, Haoda Chen, et al.
International Journal of Surgery (2023) Vol. 109, Iss. 8, pp. 2196-2203
Open Access | Times Cited: 19
Deep learning-based multimodal integration of imaging and clinical data for predicting surgical approach in percutaneous transforaminal endoscopic discectomy
Yefu Xu, Sangni Liu, Qingyi Tian, et al.
European Spine Journal (2025)
Closed Access
Contrast-enhanced CT radiomics combined with multiple machine learning algorithms for preoperative identification of lymph node metastasis in pancreatic ductal adenocarcinoma
Yue Huang, Han Zhang, Lingfeng Chen, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 2
Preoperative CA19.9 level predicts lymph node metastasis in resectable adenocarcinoma of the head of the pancreas: A further plea for biological resectability criteria
Alessandro Coppola, Vincenzo La Vaccara, Tommaso Farolfi, et al.
International Journal of Surgery (2023)
Open Access | Times Cited: 4
A machine learning model based on clinical features and ultrasound radiomics features for pancreatic tumor classification
Shunhan Yao, Dunwei Yao, Yuanxiang Huang, et al.
Frontiers in Endocrinology (2024) Vol. 15
Open Access | Times Cited: 1
Radiogenomic analysis for predicting lymph node metastasis and molecular annotation of radiomic features in pancreatic cancer
Yi Tang, Yi-xi Su, Jin-mei Zheng, et al.
Journal of Translational Medicine (2024) Vol. 22, Iss. 1
Open Access | Times Cited: 1
Computed tomography and guidelines‐based human–machine fusion model for predicting resectability of the pancreatic cancer
Adilijiang Yimamu, Jun Li, Haojie Zhang, et al.
Journal of Gastroenterology and Hepatology (2023) Vol. 39, Iss. 2, pp. 399-409
Closed Access | Times Cited: 3
CT and Guidelines based Human-machine Fusion Model for predicting resectability of the Pancreatic Cancer (Preprint)
Yi Gao, Adilijiang Yimamu, Jun Li, et al.
(2023)
Closed Access
The role of 3D modeling in pancreas surgery: a review
Александра Сергеевна Кудашкина, I. G. Kamyshanskaya, В. М. Черемисин, et al.
Diagnostic radiology and radiotherapy (2023) Vol. 14, Iss. 3, pp. 18-26
Open Access
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