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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 Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment
Young Jun Choi, Jung Hwan Baek, Hye Sun Park, et al.
Thyroid (2017) Vol. 27, Iss. 4, pp. 546-552
Closed Access | Times Cited: 189

Showing 1-25 of 189 citing articles:

A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence–Powered Ultrasound for Improving Clinical Workflow
Zeynettin Akkus, Jason Cai, Arunnit Boonrod, et al.
Journal of the American College of Radiology (2019) Vol. 16, Iss. 9, pp. 1318-1328
Open Access | Times Cited: 235
Machine learning for medical ultrasound: status, methods, and future opportunities
Laura J. Brattain, Brian A. Telfer, Manish Dhyani, et al.
Abdominal Radiology (2018) Vol. 43, Iss. 4, pp. 786-799
Open Access | Times Cited: 215
Interobserver agreement of various thyroid imaging reporting and data systems
Giorgio Grani, Livia Lamartina, Vito Cantisani, et al.
Endocrine Connections (2017) Vol. 7, Iss. 1, pp. 1-7
Open Access | Times Cited: 187
Artificial intelligence in ultrasound
Yuting Shen, Liang Chen, Wenwen Yue, et al.
European Journal of Radiology (2021) Vol. 139, pp. 109717-109717
Closed Access | Times Cited: 149
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
Breast cancer detection using deep learning techniques: challenges and future directions
Muhammad Shahid, Azhar Imran
Multimedia Tools and Applications (2025)
Closed Access | Times Cited: 3
Updates on the Management of Thyroid Cancer
Katherine Araque, Sriram Gubbi, Joanna Kłubo-Gwieździńska
Hormone and Metabolic Research (2020) Vol. 52, Iss. 08, pp. 562-577
Open Access | Times Cited: 133
Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT
Jeong Hoon Lee, Eun Ju Ha, Ju Han Kim
European Radiology (2019) Vol. 29, Iss. 10, pp. 5452-5457
Closed Access | Times Cited: 107
Machine Learning–Assisted System for Thyroid Nodule Diagnosis
Bin Zhang, Jie Tian, Shufang Pei, et al.
Thyroid (2019) Vol. 29, Iss. 6, pp. 858-867
Open Access | Times Cited: 105
Computer-aided diagnosis system for thyroid nodules on ultrasonography: diagnostic performance and reproducibility based on the experience level of operators
Eun Young Jeong, Hye Lin Kim, Eun Ju Ha, et al.
European Radiology (2018) Vol. 29, Iss. 4, pp. 1978-1985
Closed Access | Times Cited: 101
Feasibility of a 5G-Based Robot-Assisted Remote Ultrasound System for Cardiopulmonary Assessment of Patients With Coronavirus Disease 2019
Ruizhong Ye, Xianlong Zhou, Fei Shao, et al.
CHEST Journal (2020) Vol. 159, Iss. 1, pp. 270-281
Open Access | Times Cited: 93
Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound
Su Yeon Ko, Ji Hye Lee, Jung Hyun Yoon, et al.
Head & Neck (2019) Vol. 41, Iss. 4, pp. 885-891
Closed Access | Times Cited: 92
Ultrasound elastography of the thyroid: principles and current status
Chong‐Ke Zhao, Hui‐Xiong Xu
ULTRASONOGRAPHY (2018) Vol. 38, Iss. 2, pp. 106-124
Open Access | Times Cited: 91
AI applications in robotics, diagnostic image analysis and precision medicine: Current limitations, future trends, guidelines on CAD systems for medicine
Tetiana Habuza, Alramzana Nujum Navaz, Faiza Hashim, et al.
Informatics in Medicine Unlocked (2021) Vol. 24, pp. 100596-100596
Open Access | Times Cited: 89
Ultrasound image analysis using deep learning algorithm for the diagnosis of thyroid nodules
Junho Song, Young Jun Chai, Hiroo Masuoka, et al.
Medicine (2019) Vol. 98, Iss. 15, pp. e15133-e15133
Open Access | Times Cited: 85
Diagnosis of Thyroid Nodules: Performance of a Deep Learning Convolutional Neural Network Model vs. Radiologists
Vivian Youngjean Park, Kyunghwa Han, Yeong Kyeong Seong, et al.
Scientific Reports (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 81
Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training
Jeong Hoon Lee, Eun Ju Ha, Dayoung Kim, et al.
European Radiology (2020) Vol. 30, Iss. 6, pp. 3066-3072
Closed Access | Times Cited: 77
Automatic detection of tympanic membrane and middle ear infection from oto-endoscopic images via convolutional neural networks
Mohammad Azam Khan, Soonwook Kwon, Jaegul Choo, et al.
Neural Networks (2020) Vol. 126, pp. 384-394
Closed Access | Times Cited: 74
An Artificial Intelligence Model Based on ACR TI-RADS Characteristics for US Diagnosis of Thyroid Nodules
Yufan Chen, Zixiong Gao, Yanni He, et al.
Radiology (2022) Vol. 303, Iss. 3, pp. 613-619
Closed Access | Times Cited: 39
Artificial intelligence in obstetric ultrasound: A scoping review
Rebecca Horgan, Lea Nehme, Alfred Abuhamad
Prenatal Diagnosis (2023) Vol. 43, Iss. 9, pp. 1176-1219
Open Access | Times Cited: 24
Computer-Aided Diagnosis of Thyroid Nodules via Ultrasonography: Initial Clinical Experience
Young Jin Yoo, Eun Ju Ha, Yoon Joo Cho, et al.
Korean Journal of Radiology (2018) Vol. 19, Iss. 4, pp. 665-665
Open Access | Times Cited: 83
Comparison between linear and nonlinear machine-learning algorithms for the classification of thyroid nodules
Fusheng Ouyang, Baoliang Guo, Lizhu Ouyang, et al.
European Journal of Radiology (2019) Vol. 113, pp. 251-257
Closed Access | Times Cited: 72
Deep learning based classification of ultrasound images for thyroid nodules: a large scale of pilot study
Qing Guan, Yunjun Wang, Jiajun Du, et al.
Annals of Translational Medicine (2019) Vol. 7, Iss. 7, pp. 137-137
Open Access | Times Cited: 68
Deep Learning–Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study
Jeong Hoon Lee, Jung Hwan Baek, Ju Han Kim, et al.
Thyroid (2018) Vol. 28, Iss. 10, pp. 1332-1338
Closed Access | Times Cited: 61
Impact of image analysis and artificial intelligence in thyroid pathology, with particular reference to cytological aspects
Ilaria Girolami, Stefano Marletta, Liron Pantanowitz, et al.
Cytopathology (2020) Vol. 31, Iss. 5, pp. 432-444
Closed Access | Times Cited: 57
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