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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:

Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study
Xu-jun Shu, Hui Chang, Qun Wang, et al.
Clinical Neurology and Neurosurgery (2022) Vol. 219, pp. 107301-107301
Closed Access | Times Cited: 9

Showing 9 citing articles:

Preoperative Assessment of Ki‐67 Labeling Index in Pituitary Adenomas Using Delta‐Radiomics Based on Dynamic Contrast‐Enhanced MRI
Kaiyang Zhao, Chaoyue Chen, Yang Zhang, et al.
Journal of Magnetic Resonance Imaging (2025)
Closed Access | Times Cited: 1
Current status of artificial intelligence technologies in pituitary adenoma surgery: a scoping review
Seyed Farzad Maroufi, Yücel Doğruel, Ahmad Pour‐Rashidi, et al.
Pituitary (2024) Vol. 27, Iss. 2, pp. 91-128
Closed Access | Times Cited: 4
Artificial intelligence innovations in neurosurgical oncology: a narrative review
Clayton R. Baker, Matthew Pease, Daniel Sexton, et al.
Journal of Neuro-Oncology (2024) Vol. 169, Iss. 3, pp. 489-496
Open Access | Times Cited: 3
Artificial intelligence in histopathological image analysis of central nervous system tumours: A systematic review
Melanie P. Jensen, Zekai Qiang, Danyal Z. Khan, et al.
Neuropathology and Applied Neurobiology (2024) Vol. 50, Iss. 3
Open Access | Times Cited: 1
Concomitant Prediction of the Ki67 and PIT-1 Expression in Pituitary Adenoma Using Different Radiomics Models
Fangzheng Liu, Yuying Zang, Limei Feng, et al.
Deleted Journal (2024)
Closed Access | Times Cited: 1
Radiomic Applications in Skull Base Pathology: A Systematic Review of Potential Clinical Uses
Samuel A. Tenhoeve, Sydnee Lefler, Julian Brown, et al.
Journal of Neurological Surgery Part B Skull Base (2024)
Closed 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
Artificial Intelligence in Rhinology
Noel Ayoub, Jordan T. Glicksman
Otolaryngologic Clinics of North America (2024) Vol. 57, Iss. 5, pp. 831-842
Closed Access
Artificial intelligence in otolaryngology
Nathan Farrokhian, Andrés M. Bur
Elsevier eBooks (2024), pp. 109-131
Closed Access
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