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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.

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Showing 1-25 of 59 citing articles:

Diagnosis and treatment of thyroid cancer in adult patients — Recommendations of Polish Scientific Societies and the National Oncological Strategy. 2022 Update [Diagnostyka i leczenie raka tarczycy u chorych dorosłych — Rekomendacje Polskich Towarzystw Naukowych oraz Narodowej Strategii Onkologicznej. Aktualizacja na rok 2022]
Barbara Jarząb, Marek Dedecjus, Andrzej Lewiński, et al.
Endokrynologia Polska (2022) Vol. 73, Iss. 2, pp. 173-300
Open Access | Times Cited: 40
Artificial Intelligence in Thyroidology: A Narrative Review of the Current Applications, Associated Challenges, and Future Directions
David Toro-Tobón, Ricardo Loor-Torres, Mayra Durán, et al.
Thyroid (2023) Vol. 33, Iss. 8, pp. 903-917
Closed Access | Times Cited: 28
Interpretable machine learning for predicting chronic kidney disease progression risk
Jinxin Zheng, Xin Li, Jiang Zhu, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 9
Comparison of different machine learning classification models for predicting deep vein thrombosis in lower extremity fractures
Conghui Wei, Jialiang Wang, Pengfei Yu, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 7
Application of Machine Learning Techniques to Predict Bone Metastasis in Patients with Prostate Cancer
Wencai Liu, Ming-Xuan Li, Wen-Xing Qian, et al.
Cancer Management and Research (2021) Vol. Volume 13, pp. 8723-8736
Open Access | Times Cited: 40
Computed Tomography-Based Radiomics Model to Predict Central Cervical Lymph Node Metastases in Papillary Thyroid Carcinoma: A Multicenter Study
Jinɡjinɡ Li, Xinxin Wu, Ning Mao, et al.
Frontiers in Endocrinology (2021) Vol. 12
Open Access | Times Cited: 34
Application of machine learning model to predict osteoporosis based on abdominal computed tomography images of the psoas muscle: a retrospective study
Chengbin Huang, Jia-sen Hu, Kai Tan, et al.
BMC Geriatrics (2022) Vol. 22, Iss. 1
Open Access | Times Cited: 26
Development and validation of a machine learning model to predict the risk of lymph node metastasis in renal carcinoma
Xiaowei Feng, Tao Hong, Wencai Liu, et al.
Frontiers in Endocrinology (2022) Vol. 13
Open Access | Times Cited: 25
Predicting metastasis in gastric cancer patients: machine learning-based approaches
Atefeh Talebi, Carlos Celis‐Morales, Nasrin Borumandnia, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 14
Application of Machine Learning Algorithms to Predict Lymph Node Metastasis in Early Gastric Cancer
Huakai Tian, Zhikun Ning, Zhen Zong, et al.
Frontiers in Medicine (2022) Vol. 8
Open Access | Times Cited: 20
The Application of Artificial Intelligence in Thyroid Nodules: A Systematic Review Based on Bibliometric Analysis
Yun Peng, Tongtong Wang, Jingzhi Wang, et al.
Endocrine Metabolic & Immune Disorders - Drug Targets (2024) Vol. 24, Iss. 11, pp. 1280-1290
Closed Access | Times Cited: 4
Machine Learning for Thyroid Cancer Detection, Presence of Metastasis, and Recurrence Predictions—A Scoping Review
Irina-Oana Lixandru-Petre, Alexandru Dima, Mädälina Muşat, et al.
Cancers (2025) Vol. 17, Iss. 8, pp. 1308-1308
Open Access
Using Preoperative and Intraoperative Factors to Predict the Risk of Surgical Site Infections After Lumbar Spinal Surgery: A Machine Learning–Based Study
Wencai Liu, Hui Ying, Weijie Liao, et al.
World Neurosurgery (2022) Vol. 162, pp. e553-e560
Closed Access | Times Cited: 17
Exploring the Potential of Exosome-Related LncRNA Pairs as Predictors for Immune Microenvironment, Survival Outcome, and Microbiotain Landscape in Esophageal Squamous Cell Carcinoma
Fangchao Zhao, Zhirong Li, Zefang Dong, et al.
Frontiers in Immunology (2022) Vol. 13
Open Access | Times Cited: 17
Risk Prediction of Major Adverse Cardiovascular Events Occurrence Within 6 Months After Coronary Revascularization: Machine Learning Study
Jinwan Wang, Shuai Wang, Mark Xuefang Zhu, et al.
JMIR Medical Informatics (2022) Vol. 10, Iss. 4, pp. e33395-e33395
Open Access | Times Cited: 16
Predicting Mortality in Sepsis-Associated Acute Respiratory Distress Syndrome: A Machine Learning Approach Using the MIMIC-III Database
Shengtian Mu, Dongli Yan, Jie Tang, et al.
Journal of Intensive Care Medicine (2024)
Closed Access | Times Cited: 3
Machine learning in female urinary incontinence: A scoping review
Qi Wang, Xiaoxiao Wang, Xiaoxiang Jiang, et al.
Digital Health (2024) Vol. 10
Open Access | Times Cited: 3
A Comparative Analysis of Six Machine Learning Models Based on Ultrasound to Distinguish the Possibility of Central Cervical Lymph Node Metastasis in Patients With Papillary Thyroid Carcinoma
Ying Zou, Yan Shi, Jihua Liu, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 21
Unveiling the best predictive models for early‑onset metastatic cancer: Insights and innovations (Review)
Li‐Qing Yu, Zhenjun Huang, Ziqi Xiao, et al.
Oncology Reports (2024) Vol. 51, Iss. 4
Open Access | Times Cited: 2
Accurate preoperative prediction of nodal metastasis in papillary thyroid microcarcinoma: Towards optimal management of patients
Si‐Ying Lin, Meng‐Yao Li, Chi‐Peng Zhou, et al.
Head & Neck (2024) Vol. 46, Iss. 5, pp. 1009-1019
Closed Access | Times Cited: 2
The Current Progress of Artificial Intelligence in Approach to Thyroid Nodules: A Narrative Review
Parsa Yazdanpanahi, Farnaz Atighi, Alireza Keshtkar, et al.
Shiraz E-Medical Journal (2024) Vol. 25, Iss. 11
Open Access | Times Cited: 2
A comparative analysis of eight machine learning models for the prediction of lateral lymph node metastasis in patients with papillary thyroid carcinoma
Jia‐Wei Feng, Jing Ye, Gao-Feng Qi, et al.
Frontiers in Endocrinology (2022) Vol. 13
Open Access | Times Cited: 10
Machine learning algorithms are comparable to conventional regression models in predicting distant metastasis of follicular thyroid carcinoma
Yaqian Mao, Huiyu Lan, Wei Lin, et al.
Clinical Endocrinology (2022) Vol. 98, Iss. 1, pp. 98-109
Closed Access | Times Cited: 9
LASSO-based machine learning models for the prediction of central lymph node metastasis in clinically negative patients with papillary thyroid carcinoma
Jia‐Wei Feng, Jing Ye, Gao-Feng Qi, et al.
Frontiers in Endocrinology (2022) Vol. 13
Open Access | Times Cited: 9
PTC-MAS: A Deep Learning-Based Preoperative Automatic Assessment of Lymph Node Metastasis in Primary Thyroid Cancer
Ruqian Fu, Hao Yang, Dezhi Zeng, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1723-1723
Open Access | Times Cited: 5
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