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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:

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis
He-Li Xu, Tingting Gong, Fang-Hua Liu, et al.
EClinicalMedicine (2022) Vol. 53, pp. 101662-101662
Open Access | Times Cited: 83

Showing 1-25 of 83 citing articles:

Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook
Bassam Abdul Rasool Hassan, Ali Haider Mohammed, Souheil Hallit, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access | Times Cited: 2
Artificial intelligence in ovarian cancer histopathology: a systematic review
Jack Breen, Katrina J. Allen, Kieran Zucker, et al.
npj Precision Oncology (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 35
Emerging Trends in Ultrasound Education and Healthcare Clinical Applications
Manuel Duarte Lobo, Sérgio Miravent, Rui Almeida
Advances in healthcare information systems and administration book series (2024), pp. 263-287
Closed Access | Times Cited: 16
Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis
Anying Bai, Mingyu Si, Peng Xue, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 14
Artificial Intelligence in Ultrasound Diagnoses of Ovarian Cancer: A Systematic Review and Meta-Analysis
Sian Mitchell, Manolis Nikolopoulos, AbdElhamid Elzarka, et al.
Cancers (2024) Vol. 16, Iss. 2, pp. 422-422
Open Access | Times Cited: 12
Early prediction and risk stratification of ovarian cancer based on clinical data using machine learning approaches
Ting Gui, Ding Cao, Jiaxin Yang, et al.
Journal of Gynecologic Oncology (2025) Vol. 36
Open Access | Times Cited: 1
AI-enhanced PET/CT image synthesis using CycleGAN for improved ovarian cancer imaging
Amir Hossein Farshchitabrizi, Mohammad Hossein Sadeghi, Sedigheh Sina, et al.
Polish Journal of Radiology (2025) Vol. 90, pp. 26-35
Open Access | Times Cited: 1
Hybrid Vision Transformer and Xception Model for Reliable CT-Based Ovarian Neoplasms Diagnosis
Eman Hussein Alshdaifat, Hasan Gharaibeh, Amer Sindiani, et al.
Intelligence-Based Medicine (2025), pp. 100227-100227
Open Access | Times Cited: 1
Applied Artificial Intelligence in Materials Science and Material Design
Emigdio Chávez‐Ángel, Martin Eriksen, Alejandro Castro‐Álvarez, et al.
Advanced Intelligent Systems (2025)
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
Predictive Value of Machine Learning for Platinum Chemotherapy Responses in Ovarian Cancer: Systematic Review and Meta-Analysis
Qingyi Wang, Zhuo Chang, X. Liu, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e48527-e48527
Open Access | Times Cited: 7
Deep learning algorithms for melanoma detection using dermoscopic imaging: A systematic review and meta-analysis
Zichen Ye, Daqian Zhang, Yuankai Zhao, et al.
Artificial Intelligence in Medicine (2024) Vol. 155, pp. 102934-102934
Closed Access | Times Cited: 7
Ultrasound image-based nomogram combining clinical, radiomics, and deep transfer learning features for automatic classification of ovarian masses according to O-RADS
Lu Liu, Wenjun Cai, Hongyan Tian, et al.
Frontiers in Oncology (2024) Vol. 14
Open Access | Times Cited: 6
Automatic ovarian tumors recognition system based on ensemble convolutional neural network with ultrasound imaging
Shih‐Tien Hsu, Yujie Su, Chian-Huei Hung, et al.
BMC Medical Informatics and Decision Making (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 27
Ovarian cancer beyond imaging: integration of AI and multiomics biomarkers
Sepideh Hatamikia, Stéphanie Nougaret, Camilla Panico, et al.
European Radiology Experimental (2023) Vol. 7, Iss. 1
Open Access | Times Cited: 16
Revolutionizing Healthcare: The Transformative Impact of LLMs in Medicine (Preprint)
Kuo Zhang, Xiangbin Meng, Xiangyu Yan, et al.
Journal of Medical Internet Research (2024) Vol. 27, pp. e59069-e59069
Open Access | Times Cited: 6
Associating Peritoneal Metastasis With T2‐Weighted MRI Images in Epithelial Ovarian Cancer Using Deep Learning and Radiomics: A Multicenter Study
Mingxiang Wei, Yu Zhang, Cong Ding, et al.
Journal of Magnetic Resonance Imaging (2023) Vol. 59, Iss. 1, pp. 122-131
Closed Access | Times Cited: 13
Deep Learning Methods in Medical Image-Based Hepatocellular Carcinoma Diagnosis: A Systematic Review and Meta-Analysis
Qiuxia Wei, Nengren Tan, Shiyu Xiong, et al.
Cancers (2023) Vol. 15, Iss. 23, pp. 5701-5701
Open Access | Times Cited: 13
Machine learning and radiomics for segmentation and classification of adnexal masses on ultrasound
J. Barcroft, Kristofer Linton‐Reid, C. Landolfo, et al.
npj Precision Oncology (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 4
Ultrasound radiomics-based artificial intelligence model to assist in the differential diagnosis of ovarian endometrioma and ovarian dermoid cyst
Lu Liu, Wenjun Cai, Chenyang Zhou, et al.
Frontiers in Medicine (2024) Vol. 11
Open Access | Times Cited: 4
Prediction of ovarian cancer using artificial intelligence tools
Seyed Mohammad Ayyoubzadeh, Marjan Ahmadi, Alireza Banaye Yazdipour, et al.
Health Science Reports (2024) Vol. 7, Iss. 7
Open Access | Times Cited: 4
Development and interpretation of a multimodal predictive model for prognosis of gastrointestinal stromal tumor
XianHao Xiao, Xu Han, YeFei Sun, et al.
npj Precision Oncology (2024) Vol. 8, Iss. 1
Open Access | Times Cited: 4
Benefits and harms associated with the use of AI-related algorithmic decision-making systems by healthcare professionals: a systematic review
Christoph Wilhelm, Anke Steckelberg, Felix G. Rebitschek
The Lancet Regional Health - Europe (2024) Vol. 48, pp. 101145-101145
Closed Access | Times Cited: 4
Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnexal masses
Lu Liu, Wenjun Cai, Fangning Zheng, et al.
Insights into Imaging (2025) Vol. 16, Iss. 1
Open Access
Deep Learning Radiomics Nomogram Based on MRI for Differentiating between Borderline Ovarian Tumors and Stage I Ovarian Cancer: A Multicenter Study
Xinyi Wang, Quan Tao, Xiao Chu, et al.
Academic Radiology (2025)
Closed Access
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