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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 26-50 of 87 citing articles:

Fully Automatic Whole-Volume Tumor Segmentation in Cervical Cancer
Erlend Hodneland, Satheshkumar Kaliyugarasan, Kari S. Wagner‐Larsen, et al.
Cancers (2022) Vol. 14, Iss. 10, pp. 2372-2372
Open Access | Times Cited: 20
Normalization Strategies in Multi-Center Radiomics Abdominal MRI: Systematic Review and Meta-Analyses
Jovana Panić, Arianna Defeudis, Gabriella Balestra, et al.
IEEE Open Journal of Engineering in Medicine and Biology (2023) Vol. 4, pp. 67-76
Open Access | Times Cited: 11
What benefit can be obtained from magnetic resonance imaging diagnosis with artificial intelligence in prostate cancer compared with clinical assessments?
Litao Zhao, Zhenyu Liu, Wanfang Xie, et al.
Military Medical Research (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 11
Intratumoral and peritumoral radiomics predict pathological response after neoadjuvant chemotherapy against advanced gastric cancer
Chenchen Liu, Liming Li, Xingzhi Chen, et al.
Insights into Imaging (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Radiomics for osteoporosis detection – current opportunities and prospects: a literature review
Anton I. Chugaev, Yuriy А. Vasilev, A. V. Petraikin, et al.
Digital Diagnostics (2025)
Open Access
Pretreatment MRI Radiomics Based Response Prediction Model in Locally Advanced Cervical Cancer
Benedetta Gui, Rosa Autorino, Maura Miccò, et al.
Diagnostics (2021) Vol. 11, Iss. 4, pp. 631-631
Open Access | Times Cited: 24
Deep Learning Radiomics Nomogram Based on Enhanced CT to Predict the Response of Metastatic Lymph Nodes to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer
Hao Zhong, Tongyu Wang, Mingyu Hou, et al.
Annals of Surgical Oncology (2023) Vol. 31, Iss. 1, pp. 421-432
Closed Access | Times Cited: 10
Prediction of lymph node status in patients with early-stage cervical cancer based on radiomic features of magnetic resonance imaging (MRI) images
Shuyu Liu, Yu Zhou, Caizhi Wang, et al.
BMC Medical Imaging (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 9
The prognostic value of radiological and pathological lymph node status in patients with cervical cancer who underwent neoadjuvant chemotherapy and followed hysterectomy
Jianghua Lou, Xiaoxian Zhang, Jinjin Liu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 3
Sarcopenic Obesity in Cervical Carcinoma: A Strong and Independent Prognostic Factor beyond the Conventional Predictors (ESTHER Study—AFRAID Project)
Federica Medici, Martina Ferioli, S. Cammelli, et al.
Cancers (2024) Vol. 16, Iss. 5, pp. 929-929
Open Access | Times Cited: 3
Magnetic resonance imaging features of tumor and lymph node to predict clinical outcome in node-positive cervical cancer: a retrospective analysis
Shin-Hyung Park, Myong Hun Hahm, Bong Kyung Bae, et al.
Radiation Oncology (2020) Vol. 15, Iss. 1
Open Access | Times Cited: 26
Ultrasound-based radiomics: current status, challenges and future opportunities
Yingying Jia, Jun Yang, Yangyang Zhu, et al.
Medical Ultrasonography (2021) Vol. 24, Iss. 4, pp. 451-451
Open Access | Times Cited: 23
Radiomics: a quantitative imaging biomarker in precision oncology
Ashish Kumar Jha, Sneha Mithun, Nilendu Purandare, et al.
Nuclear Medicine Communications (2022) Vol. 43, Iss. 5, pp. 483-493
Open Access | Times Cited: 14
Combination of Radiomics and Machine Learning with Diffusion-Weighted MR Imaging for Clinical Outcome Prognostication in Cervical Cancer
Ankush Jajodia, Ayushi Gupta, Helmut Prosch, et al.
Tomography (2021) Vol. 7, Iss. 3, pp. 344-357
Open Access | Times Cited: 20
Predicting Disease-Free Survival With Multiparametric MRI-Derived Radiomic Signature in Cervical Cancer Patients Underwent CCRT
Bing Liu, Zhen Sun, Ziliang Xu, et al.
Frontiers in Oncology (2022) Vol. 11
Open Access | Times Cited: 13
MRI radiomics in overall survival prediction of local advanced cervical cancer patients tread by adjuvant chemotherapy following concurrent chemoradiotherapy or concurrent chemoradiotherapy alone
Guangchao Wei, Ping Jiang, Zhenchao Tang, et al.
Magnetic Resonance Imaging (2022) Vol. 91, pp. 81-90
Closed Access | Times Cited: 13
Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images
Davide Cusumano, Luca Russo, Benedetta Gui, et al.
Radiotherapy and Oncology (2022) Vol. 174, pp. 30-36
Closed Access | Times Cited: 13
Deep learning magnetic resonance imaging predicts platinum sensitivity in patients with epithelial ovarian cancer
Ruilin Lei, Yunfang Yu, Qingjian Li, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 13
A Deep Learning Radiomics Nomogram to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Cervical Cancer: A Two-Center Study
Yajiao Zhang, Chao Wu, Zhibo Xiao, et al.
Diagnostics (2023) Vol. 13, Iss. 6, pp. 1073-1073
Open Access | Times Cited: 7
Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy
Rongrong Wu, Yimin Zhou, Xingyun Xie, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 7
Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer
Mari K. Halle, Erlend Hodneland, Kari S. Wagner‐Larsen, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Multiparametric MRI-based radiomics nomogram for early prediction of pathological response to neoadjuvant chemotherapy in locally advanced gastric cancer
Jing Li, Hongkun Yin, Yi Wang, et al.
European Radiology (2022) Vol. 33, Iss. 4, pp. 2746-2756
Closed Access | Times Cited: 12
Classifying early stages of cervical cancer with MRI-based radiomics
Xin Zhao, Xueyuan Wang, Bohao Zhang, et al.
Magnetic Resonance Imaging (2022) Vol. 89, pp. 70-76
Open Access | Times Cited: 11
Comparison of MRI and CT‐Based Radiomics and Their Combination for Early Identification of Pathological Response to Neoadjuvant Chemotherapy in Locally Advanced Gastric Cancer
Jing Li, Huiling Zhang, Hongkun Yin, et al.
Journal of Magnetic Resonance Imaging (2022) Vol. 58, Iss. 3, pp. 907-923
Closed Access | Times Cited: 11
A radiomic model to classify response to neoadjuvant chemotherapy in breast cancer
Peter McAnena, Brian Moloney, Robert Browne, et al.
BMC Medical Imaging (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 11

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