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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.

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Showing 25 citing articles:

A radiomics-based interpretable machine learning model to predict the HER2 status in bladder cancer: a multicenter study
Zongjie Wei, Xuesong Bai, Yingjie Xv, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Computed tomography-based absolute delta radiomics nomogram for predicting perineural invasion in hypopharyngeal squamous cell carcinoma
Jinyan Li, Nan Jiang, Juntao Zhang, et al.
European Journal of Radiology (2025) Vol. 183, pp. 111912-111912
Closed Access
Artificial Intelligence and Radiomics in Cholangiocarcinoma: A Comprehensive Review
Marta Zerunian, Tiziano Polidori, Federica Palmeri, et al.
Diagnostics (2025) Vol. 15, Iss. 2, pp. 148-148
Open Access
Machine learning for predicting neoadjuvant chemotherapy effectiveness using ultrasound radiomics features and routine clinical data of patients with breast cancer
Pu Zhou, Hongyan Qian, Pengfei Zhu, et al.
Frontiers in Oncology (2025) Vol. 14
Open Access
Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus
Xiaofeng Wan, Yuan Wang, Ziyi Liu, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Predicting the risk of heart failure after acute myocardial infarction using an interpretable machine learning model
Qingqing Lin, Wenxiang Zhao, Hailin Zhang, et al.
Frontiers in Cardiovascular Medicine (2025) Vol. 12
Open Access
Machine learning model based on preoperative contrast-enhanced CT and clinical features to predict perineural invasion in gallbladder carcinoma patients
Hengchao Liu, Z Tang, Feng Xue, et al.
European Journal of Surgical Oncology (2025) Vol. 51, Iss. 5, pp. 109697-109697
Closed Access
Non-invasive classification of non-neoplastic and neoplastic gallbladder polyps based on clinical imaging and ultrasound radiomics features: An interpretable machine learning model
Minghui Dou, Hengchao Liu, Z Tang, et al.
European Journal of Surgical Oncology (2025) Vol. 51, Iss. 6, pp. 109709-109709
Closed Access
Survival Prediction in Brain Metastasis Patients Treated with Stereotactic Radiosurgery: A Hybrid Machine Learning Approach
Tuğçe Şençelikel, İpek Pınar Aral, Hatice Yağmur Zengin, et al.
Brain Sciences (2025) Vol. 15, Iss. 3, pp. 266-266
Open Access
Tumor-derived exosomal LINC01812 induces M2 macrophage polarization to promote perineural invasion in cholangiocarcinoma
Qinlei Wang, Zhaowei Sun, Jingyun Guo, et al.
Cancer Letters (2025) Vol. 617, pp. 217596-217596
Open Access
An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer
Lei Dai, Jinxue Yin, Xin Xin, et al.
Cancer Imaging (2025) Vol. 25, Iss. 1
Open Access
A combined radiomics and clinical model for preoperative differentiation of intrahepatic cholangiocarcinoma and intrahepatic bile duct stones with cholangitis: a machine learning approach
Hongwei Qian, Yanhua Huang, Yanbin Dong, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access
Predictive models of epidermal growth factor receptor mutation in lung adenocarcinoma using PET/CT‐based radiomics features
Zhikang Deng, Di Jin, Pei Huang, et al.
Medical Physics (2025)
Closed Access
Interpretable Machine Learning Radiomics Model Predicts 5-year Recurrence-Free Survival in Non-metastatic Clear Cell Renal Cell Carcinoma: A Multicenter and Retrospective Cohort Study
Jia Zhang, Wenxiang Huang, Li Yang, et al.
Academic Radiology (2025)
Closed Access
Improving radiologists’ diagnostic accuracy for lymphovascular invasion in colorectal cancer: insights from a multicenter CT-based study
Wenjun Diao, Kaiqi Hou, Xiaobo Chen, et al.
Abdominal Radiology (2025)
Closed Access
Diagnosis of Cholangiocarcinoma: The New Biological and Technological Horizons
Federico Selvaggi, Loris Riccardo Lopetuso, Andrea Delli Pizzi, et al.
Diagnostics (2025) Vol. 15, Iss. 8, pp. 1011-1011
Open Access
Applications of artificial intelligence in biliary tract cancers
Pankaj Gupta, Soumen Basu, Chetan Arora
Indian Journal of Gastroenterology (2024) Vol. 43, Iss. 4, pp. 717-728
Closed Access | Times Cited: 3
Development and External Validation of a CT-Based Radiomics Nomogram to Predict Perineural Invasion and Survival in Gastric Cancer: A Multi-institutional Study
Guodong Xu, Feng Feng, Wang Chen, et al.
Academic Radiology (2024)
Closed Access | Times Cited: 3
Editorial: Role of imaging in biliary tract cancer: diagnosis, staging, response prediction and image-guided therapeutics
Pankaj Gupta, Avinash Kambadakone, Bhawna Sirohi
Frontiers in Oncology (2024) Vol. 14
Open Access
Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: a multicenter cohort study: erratum

International Journal of Surgery (2024) Vol. 110, Iss. 5, pp. 3138-3138
Open Access
A radiomics model for predicting perineural invasion in stage II-III colon cancer based on computer tomography
Tairan Guo, Bing Cheng, Yunlong Li, et al.
BMC Cancer (2024) Vol. 24, Iss. 1
Open Access
Advances in radiomics applications for intrahepatic cholangiocarcinoma: a comprehensive review and future directions
Jiawei Xu, Binghua Li, Decai Yu
Hepatoma Research (2024)
Open Access
A Transcriptomic Biomarker for Predicting the Response to TACE Correlates with the Tumor Microenvironment and Radiomics Features in Hepatocellular Carcinoma
Chendong Wang, Bin Leng, Ran You, et al.
Journal of Hepatocellular Carcinoma (2024) Vol. Volume 11, pp. 2321-2337
Open Access
A Clinlabomics-Based Model Is Valuable in the Diagnosis of Hepatocellular Carcinoma with Atypical Radiological Images
Qingqing Luo, Ding-Fan Guo, Qiao-Nan Li, et al.
(2024)
Closed Access
A Machine Learning Model for the Prediction of No-Reflow Phenomenon in Acute Myocardial Infarction Using the CALLY Index
Halil Fedai, Gencay Sarıışık, Kenan Toprak, et al.
Diagnostics (2024) Vol. 14, Iss. 24, pp. 2813-2813
Open Access
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