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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:

Developing and validating ultrasound‐based radiomics models for predicting high‐risk endometrial cancer
F. Moro, Michele Albanese, Luca Boldrini, et al.
Ultrasound in Obstetrics and Gynecology (2021) Vol. 60, Iss. 2, pp. 256-268
Closed Access | Times Cited: 38

Showing 1-25 of 38 citing articles:

Role of Genomic and Molecular Biology in the Modulation of the Treatment of Endometrial Cancer: Narrative Review and Perspectives
Ilaria Cuccu, Ottavia D’Oria, Ludovica Sgamba, et al.
Healthcare (2023) Vol. 11, Iss. 4, pp. 571-571
Open Access | Times Cited: 55
Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology
Elena Jost, Philipp Kosian, J Jiménez Cruz, et al.
Journal of Clinical Medicine (2023) Vol. 12, Iss. 21, pp. 6833-6833
Open Access | Times Cited: 24
Diagnostic Accuracy of Transvaginal Ultrasound and Magnetic Resonance Imaging for the Detection of Myometrial Infiltration in Endometrial Cancer: A Systematic Review and Meta-Analysis
I. Madár, Anett Szabó, Gábor Vleskó, et al.
Cancers (2024) Vol. 16, Iss. 5, pp. 907-907
Open Access | Times Cited: 10
Application of artificial intelligence to ultrasound imaging for benign gynecological disorders: systematic review
F. Moro, Maria Teresa Giudice, Mariano Ciancia, et al.
Ultrasound in Obstetrics and Gynecology (2025)
Open Access | Times Cited: 1
Progress in the Application of Artificial Intelligence in Ultrasound-Assisted Medical Diagnosis
Yan Li, Li Q, Kang Fu, et al.
Bioengineering (2025) Vol. 12, Iss. 3, pp. 288-288
Open Access | Times Cited: 1
Role of artificial intelligence applied to ultrasound in gynecology oncology: A systematic review
F. Moro, Marianna Ciancia, Drieda Zaçe, et al.
International Journal of Cancer (2024) Vol. 155, Iss. 10, pp. 1832-1845
Open Access | Times Cited: 8
Evaluating the quality of radiomics-based studies for endometrial cancer using RQS and METRICS tools
Luca Russo, Silvia Bottazzi, Burak Koçak, et al.
European Radiology (2024) Vol. 35, Iss. 1, pp. 202-214
Open Access | Times Cited: 4
Using Radiomics and Machine Learning Applied to MRI to Predict Response to Neoadjuvant Chemotherapy in Locally Advanced Cervical Cancer
Valentina Chiappa, Giorgio Bogani, Matteo Interlenghi, et al.
Diagnostics (2023) Vol. 13, Iss. 19, pp. 3139-3139
Open Access | Times Cited: 11
Fertility Sparing in Endometrial Cancer: Where Are We Now?
Gabriele Centini, Irene Colombi, Ilaria Ianes, et al.
Cancers (2025) Vol. 17, Iss. 1, pp. 112-112
Open Access
Bibliometric research and visualization analysis of the top 100 highly cited articles on ultrasound diagnosis of endometrial cancer
Tingting Dong, Xiaohe Li, Ya Fei Wu, et al.
Asian Journal of Surgery (2025)
Open Access
Diagnosis of Malignant Endometrial Lesions from Ultrasound Radiomics Features and Clinical Variables Using Machine Learning Methods
Shanshan Li, Jiali Wang, Li Zhou, et al.
Clinical and Experimental Obstetrics & Gynecology (2025) Vol. 52, Iss. 1
Open Access
A machine learning-based 18F-FDG PET/CT multi-modality fusion radiomics model to predict Mediastinal-Hilar lymph node metastasis in NSCLC: a multi-center study
Wei Zhai, Xiaodan Li, Tengfei Zhou, et al.
Clinical Radiology (2025) Vol. 83, pp. 106832-106832
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
Ultrasound in endometrial cancer: evaluating the impact of pre-surgical staging
Mariana Rei, João Bernardes, Antónia Costa
Oncology Reviews (2025) Vol. 19
Open Access
Exploring Immune-Related Ferroptosis Genes in Thyroid Cancer: A Comprehensive Analysis
Zixuan Ru, Siwei Li, Minnan Wang, et al.
Biomedicines (2025) Vol. 13, Iss. 4, pp. 903-903
Open Access
Gated attention-enhanced vision transformer for small-sample uterine ultrasound image classification of atypical endometrial hyperplasia and endometrial cancer
Weina Wang, Zijia Liu, Chang Liu, et al.
Displays (2025), pp. 103044-103044
Closed Access
The application of ultrasound artificial intelligence in the diagnosis of endometrial diseases: Current practice and future development
Qiao Wei, Xiao Zhang, Xiaowen Liang, et al.
Digital Health (2025) Vol. 11
Open Access
Evaluating the Risk of Inguinal Lymph Node Metastases before Surgery Using the Morphonode Predictive Model: A Prospective Diagnostic Study in Vulvar Cancer Patients
Simona Maria Fragomeni, F. Moro, Fernando Palluzzi, et al.
Cancers (2023) Vol. 15, Iss. 4, pp. 1121-1121
Open Access | Times Cited: 7
The Holy Grail of obstetric ultrasound: can artificial intelligence detect hard‐to‐identify fetal cardiac anomalies?
Lior Drukker
Ultrasound in Obstetrics and Gynecology (2024) Vol. 64, Iss. 1, pp. 5-9
Closed Access | Times Cited: 2
Combined deep-learning MRI-based radiomic models for preoperative risk classification of endometrial endometrioid adenocarcinoma
Jin Yang, Yuying Cao, Fangzhu Zhou, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 6
The application of radiomics machine learning models based on multimodal MRI with different sequence combinations in predicting cervical lymph node metastasis in oral tongue squamous cell carcinoma patients
Sheng Liu, Aihua Zhang, Jianjun Xiong, et al.
Head & Neck (2023) Vol. 46, Iss. 3, pp. 513-527
Closed Access | Times Cited: 6
A multiparametric clinic-ultrasomics nomogram for predicting extremity soft-tissue tumor malignancy: a combined retrospective and prospective bicentric study
Yu Hu, Ao Li, Chong-Ke Zhao, et al.
La radiologia medica (2023) Vol. 128, Iss. 6, pp. 784-797
Closed Access | Times Cited: 4
Ultrasound based radiomics model for assessment of placental function in pregnancies with preeclampsia
Hongshuang Sun, Jing Jiao, Y. Wang, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Machine Learning Radiomics based on Intra and Peri Tumor PA/US Images Distinguish between Luminal and Non-luminal Tumors in Breast Cancers
Sijie Mo, Hui Luo, Mengyun Wang, et al.
Photoacoustics (2024) Vol. 40, pp. 100653-100653
Open Access | Times Cited: 1
Artificial intelligence in fracture detection on radiographs: a literature review
Antonio Lo Mastro, Enrico Grassi, Daniela Berritto, et al.
Japanese Journal of Radiology (2024)
Closed Access | Times Cited: 1
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