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:

Radiomics in Differentiated Thyroid Cancer and Nodules: Explorations, Application, and Limitations
Yuan Cao, Xiao Zhong, Wei Diao, et al.
Cancers (2021) Vol. 13, Iss. 10, pp. 2436-2436
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

The functional roles of the circRNA/Wnt axis in cancer
Chen Xue, Ganglei Li, Qiuxian Zheng, et al.
Molecular Cancer (2022) Vol. 21, Iss. 1
Open Access | Times Cited: 94

Advances in photoacoustic imaging aided by nano contrast agents: special focus on role of lymphatic system imaging for cancer theranostics
Badrinathan Sridharan, Hae Gyun Lim
Journal of Nanobiotechnology (2023) Vol. 21, Iss. 1
Open Access | Times Cited: 31

Artificial Intelligence in Thyroid Field—A Comprehensive Review
Fabiano Bini, Andrada Pica, Laura Azzimonti, et al.
Cancers (2021) Vol. 13, Iss. 19, pp. 4740-4740
Open Access | Times Cited: 54

The progress of radiomics in thyroid nodules
XiaoFan Gao, Xuan Ran, Wei Ding
Frontiers in Oncology (2023) Vol. 13
Open Access | Times Cited: 16

Towards in vivo photoacoustic human imaging: Shining a new light on clinical diagnostics
Zhiyang Wang, Fei Yang, Wuyu Zhang, et al.
Fundamental Research (2023) Vol. 4, Iss. 5, pp. 1314-1330
Open Access | Times Cited: 13

CT-Based Radiomics Models for Differentiation of Benign and Malignant Thyroid Nodules: A Multicenter Development and Validation Study
Shaofan Lin, Ming Gao, Zehong Yang, et al.
American Journal of Roentgenology (2024) Vol. 223, Iss. 1
Closed Access | Times Cited: 5

Identification of the Recurrence of Differentiated Thyroid Cancer by Stacking Classifier
Sulekha Das, Avijit Kumar Chaudhuri, Nobhonil Roy Choudhury, et al.
Research Square (Research Square) (2025)
Closed Access

Accuracy of Radiomics in the Identification of Extrathyroidal Extension and BRAFV600E Mutations in Papillary Thyroid Carcinoma: A Systematic Review and Meta-analysis
Yan Liu, Ling Xiang, Fei‐Fei Liu, et al.
Academic Radiology (2025) Vol. 32, Iss. 3, pp. 1385-1397
Closed Access

Diagnosis of parotid gland tumors using a ternary classification model based on ultrasound radiomics
Xiaoling Liu, Weihan Xiao, Chen Yang, et al.
Frontiers in Oncology (2025) Vol. 15
Open Access

A risk stratification model based on ultrasound radiologic features for cervical metastatic lymph nodes in papillary thyroid cancer
Hai‐Long Tan, Sai-Li Duan, Qiao He, et al.
World Journal of Surgical Oncology (2025) Vol. 23, Iss. 1
Open Access

Predicting Malignancy of Thyroid Micronodules: Radiomics Analysis Based on Two Types of Ultrasound Elastography Images
Xian‐Ya Zhang, Di Zhang, Lin-Zhi Han, et al.
Academic Radiology (2023) Vol. 30, Iss. 10, pp. 2156-2168
Closed Access | Times Cited: 10

Application of radiomics and machine learning to thyroid diseases in nuclear medicine: a systematic review
Francesco Dondi, Roberto Gatta, Giorgio Treglia, et al.
Reviews in Endocrine and Metabolic Disorders (2023) Vol. 25, Iss. 1, pp. 175-186
Open Access | Times Cited: 10

Combining radiomics with thyroid imaging reporting and data system to predict lateral cervical lymph node metastases in medullary thyroid cancer
Zhiqiang Liu, Xiwei Zhang, Xiaohui Zhao, et al.
BMC Medical Imaging (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 3

Multi-Omics and Management of Follicular Carcinoma of the Thyroid
Thifhelimbilu Emmanuel Luvhengo, I Bombil, Arian Mokhtari, et al.
Biomedicines (2023) Vol. 11, Iss. 4, pp. 1217-1217
Open Access | Times Cited: 7

Artificial intelligence in the diagnosis of thyroid cancer: Recent advances and future directions
Lakshmi Nagendra, Joseph M Pappachan, Cornelius James Fernandez
WArtificial Intelligence in Cancer (2023) Vol. 4, Iss. 1, pp. 1-10
Open Access | Times Cited: 7

Development of machine learning models to predict papillary carcinoma in thyroid nodules: The role of immunological, radiologic, cytologic and radiomic features
Luca Canali, Francesca Gaino, Andrea Costantino, et al.
Auris Nasus Larynx (2024) Vol. 51, Iss. 6, pp. 922-928
Closed Access | Times Cited: 2

Radiomics-based ultrasound models for thyroid nodule differentiation in Hashimoto’s thyroiditis
Mengyuan Fang, Mengjie Lei, Xuexue Chen, et al.
Frontiers in Endocrinology (2023) Vol. 14
Open Access | Times Cited: 3

Machine Learning: Applications and Advanced Progresses of Radiomics in Endocrine Neoplasms
Yong Wang, Liang Zhang, Lin Qi, et al.
Journal of Oncology (2021) Vol. 2021, pp. 1-17
Open Access | Times Cited: 7

Thyroid Cancer Radiomics: Navigating Challenges in a Developing Landscape
Simone Maurea, Arnaldo Stanzione, Michele Klain
Cancers (2023) Vol. 15, Iss. 24, pp. 5884-5884
Open Access | Times Cited: 2

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