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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:

Ultrasound Image Classification of Thyroid Nodules Using Machine Learning Techniques
Vijay Vyas Vadhiraj, Andrew J. Simpkin, James O’Connell, et al.
Medicina (2021) Vol. 57, Iss. 6, pp. 527-527
Open Access | Times Cited: 37

Showing 1-25 of 37 citing articles:

AI in Thyroid Cancer Diagnosis: Techniques, Trends, and Future Directions
Yassine Habchi, Yassine Himeur, Hamza Kheddar, et al.
Systems (2023) Vol. 11, Iss. 10, pp. 519-519
Open Access | Times Cited: 46
A systematic review of machine learning based thyroid tumor characterisation using ultrasonographic images
Niranjan Yadav, Rajeshwar Dass, Jitendra Virmani
Journal of Ultrasound (2024) Vol. 27, Iss. 2, pp. 209-224
Closed Access | Times Cited: 14
Research progress on artificial intelligence technology-assisted diagnosis of thyroid diseases
Lina Yang, Xinyuan Wang, Shixia Zhang, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access | Times Cited: 1
Artificial intelligence in thyroid ultrasound
Chun‐Li Cao, Qiaoli Li, Tong Jin, et al.
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 21
Enhanced-TransUNet for ultrasound segmentation of thyroid nodules
Alper Özcan, Ömür Tosun, Emrah Dönmez, et al.
Biomedical Signal Processing and Control (2024) Vol. 95, pp. 106472-106472
Closed Access | Times Cited: 7
Dual-branch network via pseudo-label training for thyroid nodule detection in ultrasound image
Ruoning Song, Chuang Zhu, Long Zhang, et al.
Applied Intelligence (2022) Vol. 52, Iss. 10, pp. 11738-11754
Closed Access | Times Cited: 22
Recent Advances in Machine Learning Applied to Ultrasound Imaging
Monica Micucci, Antonio Iula
Electronics (2022) Vol. 11, Iss. 11, pp. 1800-1800
Open Access | Times Cited: 22
Automatic classification of ultrasound thyroids images using vision transformers and generative adversarial networks
Feres JERBI, Noura Aboudi, Nawrès Khlifa
Scientific African (2023) Vol. 20, pp. e01679-e01679
Open Access | Times Cited: 11
A novel meta learning based stacked approach for diagnosis of thyroid syndrome
Muhammad Asad Abbas, Kashif Munir, Ali Raza, et al.
PLoS ONE (2024) Vol. 19, Iss. 11, pp. e0312313-e0312313
Open Access | Times Cited: 4
Advanced thyroid nodule detection using ultrasonography image analysis and bilateral mean clustering strategies
Devanand Ongole, S. Saravanan
Computers in Biology and Medicine (2025) Vol. 186, pp. 109647-109647
Closed Access
Using Deep Learning for Thyroid Nodule Risk Stratification from Ultrasound Images
Yasaman Sharifi, Morteza Danay Ashgzari, Susan Shafiei, et al.
WFUMB Ultrasound Open (2025) Vol. 3, Iss. 1, pp. 100082-100082
Open Access
Channel boosted convolutional neural network with segnet based segmentation for an automatic prediction of thyroid cancer
Leelavathi Arepalli, Venkata Rao Kasukiurthi, Madhavi Dabbiru
Soft Computing (2025)
Closed Access
GDSSA-Net: A gradually deeply supervised self-ensemble attention network for IoMT-integrated thyroid nodule segmentation
Muhammad Umar Farooq, Haris Ghafoor, Azka Rehman, et al.
Internet of Things (2025), pp. 101598-101598
Closed Access
Diagnosis of Thyroid Nodules Based on Image Enhancement and Deep Neural Networks
Xuesi Ma, Li Na Zhang
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-11
Open Access | Times Cited: 15
Efficient thyroid disorder identification with weighted voting ensemble of super learners by using adaptive synthetic sampling technique
Noor Afshan, Zohaib Mushtaq, Faten S. Alamri, et al.
AIMS Mathematics (2023) Vol. 8, Iss. 10, pp. 24274-24309
Open Access | Times Cited: 7
Automated Recognition of Cancer Tissues through Deep Learning Framework from the Photoacoustic Specimen
Gayathry S Warrier, T. M. Amirthalakshmi, K. Nimala, et al.
Contrast Media & Molecular Imaging (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 12
Hybrid deep learning assisted multi classification: Grading of malignant thyroid nodules
Mayuresh B. Gulame, Vaibhav V. Dixit
International Journal for Numerical Methods in Biomedical Engineering (2024) Vol. 40, Iss. 7
Closed Access | Times Cited: 2
TNIS: A Novel Thyroid Nodule Image Segmentation Model Based on Multi-Channel Feature Fusion
Taosheng Wei, Mingzhi Mao, Xin Wen, et al.
(2024), pp. 156-163
Closed Access | Times Cited: 1
Multifeature Fusion Classification Method for Adaptive Endoscopic Ultrasonography Tumor Image
Junke Wu, Guoliang Wei, Yaolei Wang, et al.
Ultrasound in Medicine & Biology (2023) Vol. 49, Iss. 4, pp. 937-945
Closed Access | Times Cited: 3
The Role of Machine Learning in Thyroid Cancer Diagnosis
Monika D. Kate, Vijay S. Kale
Advances in computer science research (2023), pp. 276-287
Open Access | Times Cited: 3
Development of Thyroid Disease Prediction Model in Nigeria
Terlumun Emmanuel Togor, Joshua Abah Abah, Dekera Kenneth Kwaghtyo
International Journal of Applied Information Systems (2023) Vol. 12, Iss. 41, pp. 33-47
Open Access | Times Cited: 3
Artificial Intelligence for Thyroid Disorders: A Systematic Review
Rosyid Ridlo Al Hakim, Muhammad Haikal Satria, Yanuar Z. Arief, et al.
Science in Information Technology Letters (2021) Vol. 2, Iss. 2, pp. 38-47
Open Access | Times Cited: 4
Deep Learning Method for Classifying Thyroid Nodules Using Ultrasound Images
S Pavithra, G. Yamuna, R. Arunkumar
(2022), pp. 1-6
Closed Access | Times Cited: 3
Comparison of the diagnostic effectiveness of ultrasound imaging coupled with three mathematical models for discriminating thyroid nodules
Lu Li, Hongyan Deng, Wenqin Chen, et al.
Acta Radiologica (2024) Vol. 65, Iss. 5, pp. 441-448
Closed Access
Using Regression Model Analysis for Forecasting the Likelihood of Particular Symptoms of COVID-19
Agung Pangestu, Ucu Sumirat, Rosyid Ridlo Al Hakim, et al.
SISTEMASI (2024) Vol. 13, Iss. 1, pp. 167-167
Open Access
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