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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:

Use of artificial intelligence in critical care: opportunities and obstacles
Michael R. Pinsky, Armando Bedoya, Azra Bihorac, et al.
Critical Care (2024) Vol. 28, Iss. 1
Open Access | Times Cited: 19

Showing 19 citing articles:

Exploring intensive care unit nurses' acceptance of clinical decision support systems and use of volumetric pump data: A qualitative description study
Christian Vincelette, François Martin Carrier, Charles Bilodeau, et al.
Nursing in Critical Care (2025) Vol. 30, Iss. 2
Open Access | Times Cited: 1
Should AI models be explainable to clinicians?
Gwénolé Abgrall, Andre L. Holder, Zaineb Chelly Dagdia, et al.
Critical Care (2024) Vol. 28, Iss. 1
Open Access | Times Cited: 8
Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm
Xuehui Fan, Ruixue Ye, Yan Gao, et al.
Frontiers in Artificial Intelligence (2025) Vol. 7
Open Access
Physicians’ required competencies in AI-assisted clinical settings: a systematic review
Lotte Schuitmaker, Jojanneke Drogt, Manon Benders, et al.
British Medical Bulletin (2025) Vol. 153, Iss. 1
Open Access
Rising Above the Limits of Critical Care ECMO: A Narrative Review
Pietro Bertini, Alberto Marabotti, Paolo Meani, et al.
Medicina (2025) Vol. 61, Iss. 2, pp. 174-174
Open Access
Guiding Principles for Data Sharing and Harmonization: Results of a Systematic Review and Modified Delphi From the Society of Critical Care Medicine Data Science Campaign
Donna Lee Armaignac, Smith Heavner, Michelle Rausen, et al.
Critical Care Medicine (2025)
Closed Access
Human judgment error in the intensive care unit: a perspective on bias and noise
Ilse P Peringa, Eline G. M. Cox, Renske Wiersema, et al.
Critical Care (2025) Vol. 29, Iss. 1
Open Access
AI for the hemodynamic assessment of critically ill and surgical patients: focus on clinical applications
Frédèric Michard, Marijn P. Mulder, Filipe Gonzalez, et al.
Annals of Intensive Care (2025) Vol. 15, Iss. 1
Open Access
Artificial intelligence in acute medicine: a call to action
Maurizio Cecconi, Massimiliano Greco, Benjamin Shickel, et al.
Critical Care (2024) Vol. 28, Iss. 1
Open Access | Times Cited: 2
Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry?
Abigail Ortiz, Benoit H. Mulsant
Journal of Medical Internet Research (2024) Vol. 26, pp. e59826-e59826
Open Access | Times Cited: 2
Predicting vital sign deviations during surgery from patient monitoring data: developing and validating single-stream deep learning models
Alina Dubatovka, Christoph B. Nöthiger, Donat R. Spahn, et al.
British Journal of Anaesthesia (2024) Vol. 133, Iss. 4, pp. 889-892
Closed Access | Times Cited: 1
Thy-DAMP: deep artificial neural network model for prediction of thyroid cancer mortality
Arnavaz Hajizadeh Barfejani, Mohammad Rahimi, Hassan Safdari, et al.
European Archives of Oto-Rhino-Laryngology (2024)
Closed Access
The ventilator of the future: key principles and unmet needs
John J. Marini, Luciano Gattinoni
Critical Care (2024) Vol. 28, Iss. 1
Open Access
Exploring stakeholder perceptions about using artificial intelligence for the diagnosis of rare and atypical infections
Aysun Tekin, Svetlana Herasevich, Sarah A. Minteer, et al.
Applied Clinical Informatics (2024) Vol. 16, Iss. 01, pp. 223-233
Closed Access
The Role of AI in Detecting and Mitigating Human Errors in Safety-Critical Industries: A Review
Ezgi Gursel, Mahboubeh Madadi, Jamie Coble, et al.
Reliability Engineering & System Safety (2024) Vol. 256, pp. 110682-110682
Closed Access
Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint)
Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, et al.
(2024)
Open Access
Biosignal-Based Machine Learning Predictors of Sepsis: A Mini-Review
Mateusz Szumilas
Acta Physica Polonica A (2024) Vol. 146, Iss. 4, pp. 388-393
Open Access
Deep learning for tubes and lines detection in critical illness: Generalizability and comparison with residents
Pootipong Wongveerasin, Trongtum Tongdee, Pairash Saiviroonporn
European Journal of Radiology Open (2024) Vol. 13, pp. 100593-100593
Open Access
Beyond Step Count: Are We Ready to Use Digital Phenotyping to Make Actionable Individual Predictions in Psychiatry? (Preprint)
Abigail Ortiz, Benoit H. Mulsant
(2024)
Open Access
Artificial intelligence in the intensive care unit
Thais Dias Midega, Renato Carneiro de Freitas Chaves, Ricardo Kenji Nawa, et al.
Einstein (São Paulo) (2024) Vol. 22, Iss. Suppl 2
Open Access
Trust in AI-Based Clinical Decision Support Systems Among Healthcare Workers: A Systematic Review (Preprint)
Hein Minn Tun, Hanif Abdul Rahman, Lin Naing, et al.
Journal of Medical Internet Research (2024)
Open Access
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