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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:

The Application of Artificial Intelligence and Machine Learning in Pituitary Adenomas
Congxin Dai, Bowen Sun, Renzhi Wang, et al.
Frontiers in Oncology (2021) Vol. 11
Open Access | Times Cited: 19

Showing 19 citing articles:

Role of artificial intelligence in brain tumour imaging
Ezekiel Chukwujindu, Hafsa Faiz, Sara AI-Douri, et al.
European Journal of Radiology (2024) Vol. 176, pp. 111509-111509
Closed Access | Times Cited: 6
The use of augmented reality in transsphenoidal surgery: A systematic review
Santhosh G. Thavarajasingam, Robert Vardanyan, Arian Arjomandi Rad, et al.
British Journal of Neurosurgery (2022) Vol. 36, Iss. 4, pp. 457-471
Open Access | Times Cited: 20
Predictors of Response to Treatment with First-Generation Somatostatin Receptor Ligands in Patients with Acromegaly
Montserrat Marques‐Pamies, Joan Gil, Mireia Jordà, et al.
Archives of Medical Research (2023) Vol. 54, Iss. 8, pp. 102924-102924
Open Access | Times Cited: 9
Predictors of biochemical response to somatostatin receptor ligands in acromegaly
Mónica Marazuela, Rebeca Martínez‐Hernández, Montserrat Marques‐Pamies, et al.
Best Practice & Research Clinical Endocrinology & Metabolism (2024) Vol. 38, Iss. 4, pp. 101893-101893
Open Access | Times Cited: 3
Process analysis of the patient pathway for automated data collection: an exemplar using pituitary surgery
John Hanrahan, Alexander W Carter, Danyal Z. Khan, et al.
Frontiers in Endocrinology (2024) Vol. 14
Open Access | Times Cited: 2
Establishment of a risk prediction model for olfactory disorders in patients with transnasal pituitary tumors by machine learning
Min Chen, Yuxin Li, Sumei Zhou, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Fully automated imaging protocol independent system for pituitary adenoma segmentation: a convolutional neural network—based model on sparsely annotated MRI
Martin Černý, Jan Kybic, Martin Májovský, et al.
Neurosurgical Review (2023) Vol. 46, Iss. 1
Open Access | Times Cited: 5
Integrated analysis of m6A regulator-mediated RNA methylation modification patterns and immune characteristics in Sjögren's syndrome
Junhao Yin, Jiayao Fu, Jiabao Xu, et al.
Heliyon (2024) Vol. 10, Iss. 7, pp. e28645-e28645
Open Access | Times Cited: 1
Identification of DTL as Related Biomarker and Immune Infiltration Characteristics of Nasopharyngeal Carcinoma via Comprehensive Strategies
Hehe Wang, Junge Zhang
International Journal of General Medicine (2022) Vol. Volume 15, pp. 2329-2345
Open Access | Times Cited: 5
Prognostic Models in Growth-Hormone- and Prolactin-Secreting Pituitary Neuroendocrine Tumors: A Systematic Review
Roxana-Ioana Dumitriu-Stan, Iulia Florentina Burcea, Teodor Salmen, et al.
Diagnostics (2023) Vol. 13, Iss. 12, pp. 2118-2118
Open Access | Times Cited: 2
Machine Learning Analysis of Post-Operative Tumour Progression in Non-Functioning Pituitary Neuroendocrine Tumours: A Pilot Study
Ziad Hussein, Robert W. Slack, Stephanie Baldeweg, et al.
Cancers (2024) Vol. 16, Iss. 6, pp. 1199-1199
Open Access
An objective way to predict remission and relapse in Cushing disease using Bayes’ theorem of probability
Nidhi Gupta, Konsam Biona Devi, Rama Walia, et al.
Journal of Endocrinological Investigation (2024) Vol. 47, Iss. 10, pp. 2461-2468
Closed Access
Integration of big data analytics in the investigation of the relationship between acromegaly and cancer
Pedro Iglesias, Javier Arias, Guillermo López, et al.
Endocrinología Diabetes y Nutrición (2024) Vol. 71, Iss. 8, pp. 324-331
Closed Access
Integration of big data analytics in the investigation of the relationship between acromegaly and cancer
Pedro Iglesias, Javier Arias, Guillermo López, et al.
Endocrinología Diabetes y Nutrición (English ed ) (2024) Vol. 71, Iss. 8, pp. 324-331
Closed Access
Recent advances in understanding and managing pituitary adenomas
M. Markou, Aikaterini Lavrentaki, Georgia Ntali
Faculty Reviews (2023) Vol. 12
Open Access | Times Cited: 1
Using 2-dimensional hand photographs to predict postoperative biochemical remission in acromegaly patients: a transfer learning approach
Mengqi Wang, Chengbin Duan, Shun Yao, et al.
Quantitative Imaging in Medicine and Surgery (2023) Vol. 13, Iss. 6, pp. 3747-3759
Open Access | Times Cited: 1
Radiomics and machine learning for predicting the consistency of benign tumors of the central nervous system: A systematic review
Carole Koechli, Daniel R. Zwahlen, Philippe Schucht, et al.
European Journal of Radiology (2023) Vol. 164, pp. 110866-110866
Closed Access | Times Cited: 1
Fully automated imaging protocol independent system for pituitary adenoma segmentation: A Convolutional Neural Network-based model on sparsely annotated MRI
Černý Martin, Kybic Jan, Martin Májovský, et al.
Research Square (Research Square) (2023)
Open Access
Integrated analysis of m6A regulator-mediated RNA methylation modification patterns and immune characteristics in Sjögren’s Syndrome
Junhao Yin, Jiayao Fu, Jiabao Xu, et al.
Research Square (Research Square) (2022)
Open Access
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