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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:

Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study
Ke Li, Qiandong Yao, Jingjing Xiao, et al.
Cancer Imaging (2020) Vol. 20, Iss. 1
Open Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

Artificial Intelligence to Predict Lymph Node Metastasis at CT in Pancreatic Ductal Adenocarcinoma
Yun Bian, Zhilin Zheng, Xu Fang, et al.
Radiology (2022) Vol. 306, Iss. 1, pp. 160-169
Closed Access | Times Cited: 77
Artificial intelligence in pancreatic cancer
Bowen Huang, Haoran Huang, Shuting Zhang, et al.
Theranostics (2022) Vol. 12, Iss. 16, pp. 6931-6954
Open Access | Times Cited: 72
Pancreas image mining: a systematic review of radiomics
Bassam M. Abunahel, Beau Pontré, Haribalan Kumar, et al.
European Radiology (2020) Vol. 31, Iss. 5, pp. 3447-3467
Closed Access | Times Cited: 71
Using Quantitative Imaging for Personalized Medicine in Pancreatic Cancer: A Review of Radiomics and Deep Learning Applications
Kiersten Preuss, Nate Thach, Xiaoying Liang, et al.
Cancers (2022) Vol. 14, Iss. 7, pp. 1654-1654
Open Access | Times Cited: 48
Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma
Chao An, Dongyang Li, Sheng Li, et al.
European Journal of Nuclear Medicine and Molecular Imaging (2021) Vol. 49, Iss. 4, pp. 1187-1199
Closed Access | Times Cited: 51
The impact of radiomics in diagnosis and staging of pancreatic cancer
Calogero Casà, Antonio Piras, Andrea D’Aviero, et al.
Therapeutic Advances in Gastrointestinal Endoscopy (2022) Vol. 15
Open Access | Times Cited: 29
Pancreatic cancer, radiomics and artificial intelligence
Luis Martí‐Bonmatí, Leonor Cerdá-Alberich, Alexandre Pérez‐Girbés, et al.
British Journal of Radiology (2022) Vol. 95, Iss. 1137
Open Access | Times Cited: 28
A Radiomics Nomogram for the Preoperative Prediction of Lymph Node Metastasis in Pancreatic Ductal Adenocarcinoma
Jiahao Gao, Fang Han, Yingying Jin, et al.
Frontiers in Oncology (2020) Vol. 10
Open Access | Times Cited: 33
Imaging-based Machine-learning Models to Predict Clinical Outcomes and Identify Biomarkers in Pancreatic Cancer
Boris V. Janssen, S. Verhoef, Nina J. Wesdorp, et al.
Annals of Surgery (2021) Vol. 275, Iss. 3, pp. 560-567
Closed Access | Times Cited: 28
Prediction of Response to Anti-Angiogenic Treatment for Advanced Colorectal Cancer Patients: From Biological Factors to Functional Imaging
Giuseppe Corrias, Eleonora Lai, Pina Ziranu, et al.
Cancers (2024) Vol. 16, Iss. 7, pp. 1364-1364
Open Access | Times Cited: 4
A time-dependent explainable radiomic analysis from the multi-omic cohort of CPTAC-Pancreatic Ductal Adenocarcinoma
Gian Maria Zaccaria, Francesco Berloco, Domenico Buongiorno, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 257, pp. 108408-108408
Open Access | Times Cited: 4
A dual-transformation with contrastive learning framework for lymph node metastasis prediction in pancreatic cancer
Xiahan Chen, Weishen Wang, Yu Jiang, et al.
Medical Image Analysis (2023) Vol. 85, pp. 102753-102753
Closed Access | Times Cited: 10
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: 3
A CT-based radiomics nomogram for the preoperative prediction of perineural invasion in pancreatic ductal adenocarcinoma
Yan Deng, Haopeng Yu, Xiuping Duan, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access
Deep Learning for Lymph Node Metastasis Detection in Pancreatic Ductal Adenocarcinoma
David Dueñas Gaviria, Patrick Kupczyk, Belinda Lee, et al.
Lecture notes in electrical engineering (2025), pp. 66-76
Closed Access
Personalized Medical Approach in Gastrointestinal Surgical Oncology: Current Trends and Future Perspectives
Dae Hoon Kim
Journal of Personalized Medicine (2025) Vol. 15, Iss. 5, pp. 175-175
Open Access
Basic pancreatic lesions: Radiologic-pathologic correlation
Yun Bian, Hui Jiang, Jianming Zheng, et al.
Journal of Translational Internal Medicine (2022) Vol. 10, Iss. 1, pp. 18-27
Open Access | Times Cited: 15
Radiomics nomogram for predicting axillary lymph node metastasis in breast cancer based on DCE-MRI: A multicenter study
Jiwen Zhang, Zhongsheng Zhang, Ning Mao, et al.
Journal of X-Ray Science and Technology (2023) Vol. 31, Iss. 2, pp. 247-263
Closed Access | Times Cited: 9
Pancreatic ductal adenocarcinoma staging: A narrative review of radiologic techniques and advances
Linda C. Chu, Elliot K. Fishman
International Journal of Surgery (2023)
Open Access | Times Cited: 8
Radiomics advances in the evaluation of pancreatic cystic neoplasms
Kuan-Zheng Mao, Chao Ma, Bin Song
Heliyon (2024) Vol. 10, Iss. 3, pp. e25535-e25535
Open Access | Times Cited: 3
Characterization of Benign and Malignant Pancreatic Lesions with DECT Quantitative Metrics and Radiomics
Shadi Ebrahimian, Ramandeep Singh, Arjunlokesh Netaji, et al.
Academic Radiology (2021) Vol. 29, Iss. 5, pp. 705-713
Closed Access | Times Cited: 19
Predictive role of radiomics features extracted from preoperative cross-sectional imaging of pancreatic ductal adenocarcinoma in detecting lymph node metastasis: a systemic review and meta-analysis
Mohammad Mirza‐Aghazadeh‐Attari, Seyedeh Panid Madani, Haneyeh Shahbazian, et al.
Abdominal Radiology (2023) Vol. 48, Iss. 8, pp. 2570-2584
Closed Access | Times Cited: 7
The Utility of Artificial Intelligence in the Diagnosis and Management of Pancreatic Cancer
Vikash Kumar, Mrunanjali Gaddam, Amr A. Moustafa, et al.
Cureus (2023)
Open Access | Times Cited: 7
Peritumoral and Intratumoral Texture Features Based on Multiparametric MRI and Multiple Machine Learning Methods to Preoperatively Evaluate the Pathological Outcomes of Pancreatic Cancer
Ni Xie, Xuhui Fan, Desheng Chen, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 58, Iss. 2, pp. 379-391
Closed Access | Times Cited: 12
Dendritic cell vaccination combined with irreversible electroporation for treating pancreatic cancer—a narrative review
Zigeng Zhang, Guangbo Yu, Aydιn Eresen, et al.
Annals of Translational Medicine (2024) Vol. 12, Iss. 4, pp. 77-77
Open Access | Times Cited: 2
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