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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:

Machine learning versus regression for prediction of sporadic pancreatic cancer
Wansu Chen, Botao Zhou, Christie Y. Jeon, et al.
Pancreatology (2023) Vol. 23, Iss. 4, pp. 396-402
Open Access | Times Cited: 15

Showing 15 citing articles:

survex: an R package for explaining machine learning survival models
Mikołaj Spytek, Mateusz Krzyziński, S. Langbein, et al.
Bioinformatics (2023) Vol. 39, Iss. 12
Open Access | Times Cited: 22
Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review
Victoria Moglia, Owen Johnson, G. Elliott Cook, et al.
BMC Medical Research Methodology (2025) Vol. 25, Iss. 1
Open Access | Times Cited: 1
Biomarkers, Omics and Artificial Intelligence for Early Detection of Pancreatic Cancer.
Kate Murray, Lucy Oldfield, Irena Stefanova, et al.
Seminars in Cancer Biology (2025) Vol. 111, pp. 76-88
Closed Access | Times Cited: 1
The role of biomarkers in the early detection of pancreatic cancer
Michael Goggins
Familial Cancer (2024) Vol. 23, Iss. 3, pp. 309-322
Open Access | Times Cited: 5
From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction
Riccardo Farinella, Alessio Felici, Giulia Peduzzi, et al.
Seminars in Cancer Biology (2025)
Open Access
Artificial Intelligence to predict cancer risk, are we there yet? a comprehensive review across cancer types
Alessio Felici, Giulia Peduzzi, Roberto Pellungrini, et al.
European Journal of Cancer (2025), pp. 115440-115440
Closed Access
Machine Learning Models for Pancreatic Cancer Risk Prediction Using Electronic Health Record Data—A Systematic Review and Assessment
Anup Kumar Mishra, Bradford Chong, Shivaram P. Arunachalam, et al.
The American Journal of Gastroenterology (2024) Vol. 119, Iss. 8, pp. 1466-1482
Closed Access | Times Cited: 3
Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model
Dong‐yue Wen, Jiamin Chen, Zhiping Tang, et al.
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 3
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: 3
Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank
Giulia Peduzzi, Alessio Felici, Roberto Pellungrini, et al.
Digestive and Liver Disease (2024)
Closed Access | Times Cited: 3
Establishment of prediction model for mortality risk of pancreatic cancer: a retrospective study
Raoof Nopour
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Machine learning to predict completion of treatment for pancreatic cancer
Shamsher A. Pasha, Abdullah Khalid, Todd Levy, et al.
Journal of Surgical Oncology (2024)
Closed Access | Times Cited: 1
Machine learning analysis/optimization of auxetic performance of a polymeric meta-hybrid structure of re-entrant and meta-trichiral
Xiangning Zhou, Yuchi Leng, Ashit Kumar Dutta, et al.
European Journal of Mechanics - A/Solids (2024), pp. 105463-105463
Closed Access | Times Cited: 1
External UK validation of the ENDPAC model to predict pancreatic cancer risk: A registered report protocol
Claire A. Price, Hugh Claridge, Simon de Lusignan, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
A machine-learning prediction model to identify risk of firearm injury using electronic health records data
Hui Zhou, Claudia Nau, Fagen Xie, et al.
Journal of the American Medical Informatics Association (2024) Vol. 31, Iss. 10, pp. 2173-2180
Closed Access
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