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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 State of Machine Learning in Spine Surgery
Edward M. DelSole, Wyatt L. Keck, Aalpen A. Patel
Clinical Spine Surgery A Spine Publication (2021) Vol. 35, Iss. 2, pp. 80-89
Closed Access | Times Cited: 10

Showing 10 citing articles:

Machine learning predictive models for acute pancreatitis: A systematic review
You Zhou, Yutong Ge, Xiaolei Shi, et al.
International Journal of Medical Informatics (2021) Vol. 157, pp. 104641-104641
Open Access | Times Cited: 55
The value of machine learning technology and artificial intelligence to enhance patient safety in spine surgery: a review
Fatemeh Arjmandnia, Ehsan Alimohammadi
Patient Safety in Surgery (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 7
Clinical Decision Support System Used in Spinal Disorders: Scoping Review
Zheng An Toh, Bjørnar Berg, Qin Han, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e53951-e53951
Open Access | Times Cited: 5
Advancements in Artificial Intelligence for Foot and Ankle Surgery: A Systematic Review
Puneet Gupta, Kiera A. Kingston, Martin O’Malley, et al.
Foot & Ankle Orthopaedics (2023) Vol. 8, Iss. 1
Open Access | Times Cited: 11
Assessing the predictive capability of machine learning models in determining clinical outcomes for patients with cervical spondylotic myelopathy treated with laminectomy and posterior spinal fusion
Ehsan Alimohammadi, Elnaz Fatahi, Alireza Abdi, et al.
Patient Safety in Surgery (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 3
The use of machine learning for predicting candidates for outpatient spine surgery: a review
Ian J. Wellington, Owen P. Karsmarski, Kyle V. Murphy, et al.
Journal of Spine Surgery (2023) Vol. 9, Iss. 3, pp. 323-330
Open Access | Times Cited: 3
Leveraging machine learning to develop a postoperative predictive model for postoperative urinary retention following lumbar spine surgery
Samuel L. Malnik, Ken Porche, Yusuf Mehkri, et al.
Frontiers in Neurology (2024) Vol. 15
Open Access
Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules
Yechan Seo, Seoi Jeong, Joongku Lee, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access
Machine Learning Models Leveraging Smartphone-Based Patient Mobility Data Can Accurately Predict Functional Outcomes After Spine Surgery
Hasan S. Ahmad, Daksh Chauhan, Mert Marcel Dagli, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 21, pp. 6515-6515
Open Access
Predictive accuracy of machine learning models for conservative treatment failure in thoracolumbar burst fractures
Ehsan Alimohammadi, Fatemeh Arjmandnia, Mohammadali Ataee, et al.
BMC Musculoskeletal Disorders (2024) Vol. 25, Iss. 1
Open Access
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