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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:

Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening
Andrew A. S. Soltan, Jenny Yang, Ravi Pattanshetty, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 4, pp. e266-e278
Open Access | Times Cited: 40

Showing 1-25 of 40 citing articles:

Machine learning generalizability across healthcare settings: insights from multi-site COVID-19 screening
Jenny Yang, Andrew A. S. Soltan, David A. Clifton
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 88
An adversarial training framework for mitigating algorithmic biases in clinical machine learning
Jenny Yang, Andrew A. S. Soltan, David W. Eyre, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 56
Algorithmic fairness and bias mitigation for clinical machine learning with deep reinforcement learning
Jenny Yang, Andrew A. S. Soltan, David W. Eyre, et al.
Nature Machine Intelligence (2023) Vol. 5, Iss. 8, pp. 884-894
Open Access | Times Cited: 52
Machine Learning in Laboratory Medicine: Recommendations of the IFCC Working Group
Stephen R. Master, Tony Badrick, Andreas Bietenbeck, et al.
Clinical Chemistry (2023) Vol. 69, Iss. 7, pp. 690-698
Closed Access | Times Cited: 26
Deep reinforcement learning for multi-class imbalanced training: applications in healthcare
Jenny Yang, Rasheed El-Bouri, Odhran O’Donoghue, et al.
Machine Learning (2023) Vol. 113, Iss. 5, pp. 2655-2674
Open Access | Times Cited: 21
A scalable federated learning solution for secondary care using low-cost microcomputing: privacy-preserving development and evaluation of a COVID-19 screening test in UK hospitals
Andrew A. S. Soltan, Anshul Thakur, Jenny Yang, et al.
The Lancet Digital Health (2024) Vol. 6, Iss. 2, pp. e93-e104
Open Access | Times Cited: 14
Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers
Amir Kamel Rahimi, Oliver Pienaar, Moji Ghadimi, et al.
Journal of Medical Internet Research (2024) Vol. 26, pp. e49655-e49655
Open Access | Times Cited: 7
The influence of birthweight on mortality and severe neonatal morbidity in late preterm and term infants: an Australian cohort study
Tegan Triggs, Kylie Crawford, Jesrine Hong, et al.
The Lancet Regional Health - Western Pacific (2024) Vol. 45, pp. 101054-101054
Open Access | Times Cited: 7
Generalizability assessment of AI models across hospitals in a low-middle and high income country
Jenny Yang, Nguyen Thanh Dung, Phạm Ngọc Thạch, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 5
Artificial Intelligence in the Intensive Care Unit: Current Evidence on an Inevitable Future Tool
Vinay Suresh, Kaushal Singh, Esha Vaish, et al.
Cureus (2024)
Open Access | Times Cited: 4
Machine Learning First Response to COVID-19: A Systematic Literature Review of Clinical Decision Assistance Approaches during Pandemic Years from 2020 to 2022
Goizalde Badiola-Zabala, José Manuel López-Guede, Julián Estévez, et al.
Electronics (2024) Vol. 13, Iss. 6, pp. 1005-1005
Open Access | Times Cited: 3
Improving the performance of machine learning algorithms for health outcomes predictions in multicentric cohorts
Roberta Moreira Wichmann, Fernando Timoteo Fernandes, Alexandre Dias Porto Chiavegatto Filho, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 9
Experiences of using artificial intelligence in healthcare: a qualitative study of UK clinician and key stakeholder perspectives
Carol-Ann Fazakarley, Maria Breen, Paul Leeson, et al.
BMJ Open (2023) Vol. 13, Iss. 12, pp. e076950-e076950
Open Access | Times Cited: 9
The Two Sides of the COVID-19 Pandemic
Ravinder Kumar, Vartika Srivastava, Kripa N. Nand
COVID (2023) Vol. 3, Iss. 12, pp. 1746-1760
Open Access | Times Cited: 7
Mitigating machine learning bias between high income and low–middle income countries for enhanced model fairness and generalizability
Jenny Yang, Lei Clifton, Nguyen Thanh Dung, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 2
Scalable federated learning for emergency care using low cost microcomputing: Real-world, privacy preserving development and evaluation of a COVID-19 screening test in UK hospitals
Andrew A. S. Soltan, Anshul Thakur, Jenny Yang, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 6
Generalizability Assessment of AI Models Across Hospitals: A Comparative Study in Low-Middle Income and High Income Countries
Jenny Yang, Nguyen Thanh Dung, Phạm Ngọc Thạch, et al.
medRxiv (Cold Spring Harbor Laboratory) (2023)
Open Access | Times Cited: 6
Automation in Contemporary Clinical Information Systems: a Survey of AI in Healthcare Settings
Farah Magrabi, David Lyell, Enrico Coiera
Yearbook of Medical Informatics (2023) Vol. 32, Iss. 01, pp. 115-126
Open Access | Times Cited: 6
Symptom‐based case definitions for COVID‐19: Time and geographical variations for detection at hospital admission among 260,000 patients
Joaquín Baruch, Amanda Rojek, Christiana Kartsonaki, et al.
Influenza and Other Respiratory Viruses (2022) Vol. 16, Iss. 6, pp. 1040-1050
Open Access | Times Cited: 8
Addressing label noise for electronic health records: insights from computer vision for tabular data
Jenny Yang, Hagen Triendl, Andrew A. S. Soltan, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 1
Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare
Anshul Thakur, Soheila Molaei, Pafue Christy Nganjimi, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 1
Effectiveness of an artificial intelligence-based training and monitoring system in prevention of nosocomial infections: A pilot study of hospital-based data
Ting Huang, Yue Ma, Shaxi Li, et al.
Drug Discoveries & Therapeutics (2023) Vol. 17, Iss. 5, pp. 351-356
Open Access | Times Cited: 4
Perceptions and concerns of emergency medicine practitioners about artificial intelligence in emergency triage management during the pandemic: a national survey-based study
Erhan Ahun, Ahmet Duran Demir, Yavuz Yiğit, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 4
Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: A New Utility for Deep Reinforcement Learning
Jenny Yang, Andrew A. S. Soltan, David A. Clifton
medRxiv (Cold Spring Harbor Laboratory) (2022)
Open Access | Times Cited: 6
COVID-19 rapid molecular point-of-care testing is effective and cost-beneficial for the acute care of trauma patients
Josef Stolberg-Stolberg, Elena Jacob, Joachim Kuehn, et al.
European Journal of Trauma and Emergency Surgery (2022) Vol. 49, Iss. 1, pp. 487-493
Open Access | Times Cited: 6
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