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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:

A Deep Learning Framework for the Prediction and Diagnosis of Ovarian Cancer in Pre- and Post-Menopausal Women
Blessed Ziyambe, Abid Yahya, Tawanda Mushiri, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1703-1703
Open Access | Times Cited: 36

Showing 1-25 of 36 citing articles:

Smart Transportation Systems
Muhammad Usman Tariq
Advances in civil and industrial engineering book series (2024), pp. 254-283
Closed Access | Times Cited: 30
Deep learning in ovarian cancer diagnosis: a comprehensive review of various imaging modalities
Mohammad Hossein Sadeghi, Sedigheh Sina, Hamid Omidi, et al.
Polish Journal of Radiology (2024) Vol. 89, pp. 30-48
Open Access | Times Cited: 16
Integration of IoMT for Enhanced Healthcare
Muhammad Usman Tariq
Advances in medical technologies and clinical practice book series (2024), pp. 70-95
Closed Access | Times Cited: 16
Screening ovarian cancer by using risk factors: machine learning assists
Raoof Nopour
BioMedical Engineering OnLine (2024) Vol. 23, Iss. 1
Open Access | Times Cited: 10
Cultivating Cultural Intelligence for the Global Workforce
Muhammad Usman Tariq
Advances in higher education and professional development book series (2024), pp. 297-332
Closed Access | Times Cited: 5
From Data to Decisions
Subhadip Kowar, Tulika Paul, Nilav Darsan Mukhopadhayay, et al.
Advances in environmental engineering and green technologies book series (2025), pp. 1-22
Closed Access
A Review of Deep Learning Models for Early Detection and Diagnosis of Ovarian Cancer
D. K. Savitha, D. Rajakumari
International Research Journal of Multidisciplinary Technovation (2025), pp. 123-137
Open Access
OVision A raspberry Pi powered portable low cost medical device framework for cancer diagnosis
Sameer Mehta
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
Histopathological Deep Learning: Exploring Ovarian Cancer Subtypes with Image Analysis
Lakshmi V. Ramanathan, Kirby Rachel, Sai Loukya Namineni, et al.
SSRN Electronic Journal (2025)
Closed Access
Machine learning use in early ovarian cancer detection
Emmanuel Kokori, Nicholas Aderinto, Gbolahan Olatunji, et al.
Deleted Journal (2025) Vol. 2, Iss. 1
Open Access
Artificial Intelligence for Ovarian Cancer Detection with Medical Images: A Review of the Last Decade (2013–2023)
Amir Reza Naderi Yaghouti, Ahmad Shalbaf, Roohallah Alizadehsani, et al.
Archives of Computational Methods in Engineering (2025)
Closed Access
Explainable AI-based feature importance analysis for ovarian cancer classification with ensemble methods
Ashwini Kodipalli, V. Susheela Devi, Shyamala Guruvare, et al.
Frontiers in Public Health (2025) Vol. 13
Open Access
Improved Prediction of Ovarian Cancer Using Ensemble Classifier and Shaply Explainable AI
Nihal Abuzinadah, Sarath Kumar Posa, Aisha Ahmed Alarfaj, et al.
Cancers (2023) Vol. 15, Iss. 24, pp. 5793-5793
Open Access | Times Cited: 7
Preoperative Molecular Subtype Classification Prediction of Ovarian Cancer Based on Multi-Parametric Magnetic Resonance Imaging Multi-Sequence Feature Fusion Network
Yijiang Du, Tingting Wang, Linhao Qu, et al.
Bioengineering (2024) Vol. 11, Iss. 5, pp. 472-472
Open Access | Times Cited: 2
A deep learning approach for ovarian cancer detection and classification based on fuzzy deep learning
Eman I. Abd El-Latif, M. A. El-Dosuky, Ashraf Darwish, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
DeepOvaNet: A Comprehensive Deep Learning Framework for Predicting and Diagnosing Ovarian Cancer in Women Across Menopausal Transitions
Ashis Das, M Chilakarao, Preesat Biswas, et al.
(2024), pp. 1-7
Closed Access | Times Cited: 1
Artificial Intelligence Trends and Tools for Improving Women’s Health
Shivangi Mishra, A. Sandhya Rani, Vipin Pal
Journal of Women’s Health Care and Management (2024) Vol. 5, Iss. 2
Open Access | Times Cited: 1
Selective feature-based ovarian cancer prediction using MobileNet and explainable AI to manage women healthcare
Nouf Abdullah Almujally, Abdulrahman Alzahrani, A. Hakeem, et al.
Multimedia Tools and Applications (2024)
Closed Access | Times Cited: 1
Deep fine-KNN classification of ovarian cancer subtypes using efficientNet-B0 extracted features: a comprehensive analysis
Santi Kumari Behera, Ashis Das, Prabira Kumar Sethy
Journal of Cancer Research and Clinical Oncology (2024) Vol. 150, Iss. 7
Open Access | Times Cited: 1
Comprehensive analysis of artificial intelligence techniques for gynaecological cancer: symptoms identification, prognosis and prediction
Sonam Gandotra, Yogesh Kumar, Nandini Modi, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 8
Open Access | Times Cited: 1
New Trends in Ovarian Cancer Diagnosis Using Deep Learning: A Systematic Review
Mohamed El-Khatib, Dan Popescu, Oana Mihaela Teodor, et al.
IEEE Access (2024) Vol. 12, pp. 116587-116608
Open Access | Times Cited: 1
Improved rank-based recursive feature elimination method based ovarian cancer detection model via customized deep architecture
Namani Deepika Rani, Mahesh Babu
Computer Methods and Programs in Biomedicine (2024) Vol. 256, pp. 108358-108358
Closed Access | Times Cited: 1
Intelligent system based on multiple networks for accurate ovarian tumor semantic segmentation
Mohamed El-Khatib, Dan Popescu, Oana Mihaela Teodor, et al.
Heliyon (2024) Vol. 10, Iss. 17, pp. e37386-e37386
Open Access | Times Cited: 1
Enhanced ovarian cancer survival prediction using temporal analysis and graph neural networks
G S Pradeep Ghantasala, Dilip Kumar, Pellakuri Vidyullatha, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Hybrid Feature Extraction for Breast Cancer Classification Using the Ensemble Residual VGG16 Deep Learning Model
Zhenfei Wang, Muhammad Mumtaz Ali, Kashif Iqbal Sahibzada, et al.
Current Bioinformatics (2024) Vol. 20, Iss. 2, pp. 149-163
Closed Access | Times Cited: 1
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