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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:

Systematic review and longitudinal analysis of implementing Artificial Intelligence to predict clinical deterioration in adult hospitals: what is known and what remains uncertain
Anton van der Vegt, Victoria Campbell, Imogen Mitchell, et al.
Journal of the American Medical Informatics Association (2023) Vol. 31, Iss. 2, pp. 509-524
Open Access | Times Cited: 12

Showing 12 citing articles:

Prioritising deteriorating patients using time-to-event analysis: prediction model development and internal–external validation
Robin Blythe, Rex Parsons, Adrian Barnett, et al.
Critical Care (2024) Vol. 28, Iss. 1
Open Access | Times Cited: 9
Factors underpinning the performance of implemented artificial intelligence-based patient deterioration prediction systems: reasons for selection and implications for hospitals and researchers
Anton van der Vegt, Victoria Campbell, Shuyi Wang, et al.
Journal of the American Medical Informatics Association (2025) Vol. 32, Iss. 3, pp. 492-509
Open Access
Clinical evaluation of a machine learning–based early warning system for patient deterioration
Amol A. Verma, Thérèse A. Stukel, Michael Colacci, et al.
Canadian Medical Association Journal (2024) Vol. 196, Iss. 30, pp. E1027-E1037
Open Access | Times Cited: 4
AI's deep dive into complex pediatric inguinal hernia issues: a challenge to traditional guidelines?
Guoyong Wang, Qinde Liu, G Chen, et al.
Hernia (2023) Vol. 27, Iss. 6, pp. 1587-1599
Closed Access | Times Cited: 8
Why clinical artificial intelligence is (almost) non‐existent in Australian hospitals and how to fix it
Anton van der Vegt, Victoria Campbell, Guido Zuccon
The Medical Journal of Australia (2023) Vol. 220, Iss. 4, pp. 172-175
Open Access | Times Cited: 5
Moving From In Silico to In Clinico Evaluations of Machine Learning-Based Interventions in Critical Care*
Gary E. Weissman
Critical Care Medicine (2024) Vol. 52, Iss. 7, pp. 1141-1144
Open Access | Times Cited: 1
Toward the Rigorous Evaluation of Early Warning Scores
Amol A. Verma
JAMA Network Open (2024) Vol. 7, Iss. 10, pp. e2438966-e2438966
Open Access | Times Cited: 1
Clinician perspectives and recommendations regarding design of clinical prediction models for deteriorating patients in acute care
Robin Blythe, Sundresan Naicker, Nicole White, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access
Patient Deterioration Prediction Models Using Nursing Documentation Patterns as Predictors: A Reproducibility and Generalizability Study Across a Large Number of Hospitals Across the United States
Yik-Ki Jacob Wan, Samir Abdelrahman, Julio C. Facelli, et al.
(2024)
Closed Access
Real-Time Clinical Decision Support Systems for the Prevention of Deterioration in Acute Care
Robin Blythe
(2024)
Open Access
Sociodemographic bias in clinical machine learning models: A scoping review of algorithmic bias instances and mechanisms
Michael Colacci, Yu Qing Huang, Gemma Postill, et al.
Journal of Clinical Epidemiology (2024) Vol. 178, pp. 111606-111606
Closed Access
Explainable machine learning to identify patients at risk of developing hospital acquired infections
Andrew P. Creagh, Tom Pease, Pat Ashworth, et al.
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access
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