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:

A Comparison of Veterans with Problematic Opioid Use Identified through Natural Language Processing of Clinical Notes versus Using Diagnostic Codes
T. Elizabeth Workman, Joel Kupersmith, Phillip Ma, et al.
Healthcare (2024) Vol. 12, Iss. 7, pp. 799-799
Open Access | Times Cited: 6

Showing 6 citing articles:

A deep learning analysis for dual healthcare system users and risk of opioid use disorder
Ying Yin, Elizabeth Workman, Phillip Ma, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access

Zero-Shot Extraction of Seizure Outcomes from Clinical Notes Using Generative Pretrained Transformers
William K.S. Ojemann, Kevin Xie, Kevin Liu, et al.
Journal of Healthcare Informatics Research (2025)
Open Access

Artificial Intelligence-driven and technological innovations in the diagnosis and management of substance use disorders
Daniela Lé Tassinari, Maria Olívia Pozzolo Pedro, Manoela Pozzolo Pedro, et al.
International Review of Psychiatry (2024), pp. 1-7
Closed Access | Times Cited: 2

Dual Healthcare System Users and Risk of Opioid Use Disorder: A Deep Learning analysis
Ying Yin, Elizabeth Workman, Phillip Ma, et al.
Research Square (Research Square) (2024)
Open Access

Zero-shot extraction of seizure outcomes from clinical notes using generative pretrained transformers
William K.S. Ojemann, Kevin Xie, Kevin Liu, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access

More than the Sum of its Parts: Applying Topic Modeling and Explainable AI to Deep Learning in Understanding Problematic Opioid Use
T. Elizabeth Workman, Joel Kupersmith, Ying Yin, et al.
2021 IEEE International Conference on Big Data (Big Data) (2024), pp. 4058-4067
Closed Access

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