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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:

Solving the explainable AI conundrum by bridging clinicians’ needs and developers’ goals
Nadine Bienefeld, J. M. Boss, Rahel Lüthy, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

FDA-Approved Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices: An Updated Landscape
Geeta Joshi, Aditi Jain, Shalini Reddy Araveeti, et al.
Electronics (2024) Vol. 13, Iss. 3, pp. 498-498
Open Access | Times Cited: 96
Explainable Artificial Intelligence for Drug Discovery and Development: A Comprehensive Survey
Roohallah Alizadehsani, Solomon Sunday Oyelere, Sadiq Hussain, et al.
IEEE Access (2024) Vol. 12, pp. 35796-35812
Open Access | Times Cited: 21
Digital twins as global learning health and disease models for preventive and personalized medicine
Xinxiu Li, Joseph Loscalzo, A. K. M. Firoj Mahmud, et al.
Genome Medicine (2025) Vol. 17, Iss. 1
Open Access | Times Cited: 2
Advancing AI in healthcare: A comprehensive review of best practices
Sergei Polevikov
Clinica Chimica Acta (2023) Vol. 548, pp. 117519-117519
Closed Access | Times Cited: 33
The clinician-AI interface: intended use and explainability in FDA-cleared AI devices for medical image interpretation
Stephanie L. McNamara, Paul H. Yi, William Lotter
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 10
Explainable AI: Bridging the Gap between Machine Learning Models and Human Understanding
Rajiv Avacharmal, Ai Ml, Risk Lead
Journal of Informatics Education and Research (2024)
Open Access | Times Cited: 9
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
Orchestrating explainable artificial intelligence for multimodal and longitudinal data in medical imaging
Aurélie Pahud de Mortanges, Haozhe Luo, Shelley Zixin Shu, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 7
A framework for integrating artificial intelligence for clinical care with continuous therapeutic monitoring
Emma Chen, Shvetank Prakash, Vijay Janapa Reddi, et al.
Nature Biomedical Engineering (2023)
Closed Access | Times Cited: 19
Quantifying the impact of AI recommendations with explanations on prescription decision making
Myura Nagendran, Paul Festor, Matthieu Komorowski, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 18
Mental stress detection from ultra-short heart rate variability using explainable graph convolutional network with network pruning and quantisation
V. Adarsh, G. R. Gangadharan
Machine Learning (2024) Vol. 113, Iss. 8, pp. 5467-5494
Closed Access | Times Cited: 5
Graph Artificial Intelligence in Medicine
Ruth Johnson, Michelle M. Li, Ayush Noori, et al.
Annual Review of Biomedical Data Science (2024) Vol. 7, Iss. 1, pp. 345-368
Open Access | Times Cited: 5
Interpretable AI for medical image analysis: methods, evaluation, and clinical considerations
Tiago Gonçalves, Anna Hedström, Aurélie Pahud de Mortanges, et al.
Elsevier eBooks (2025), pp. 315-346
Closed Access
Generalized reinforcement learning control algorithm for fully automated insulin delivery system
Vega Pradana Rachim, J. Yoo, Jaeyeon Lee, et al.
Expert Systems with Applications (2025), pp. 126909-126909
Closed Access
Artificial Intelligence Applications in Cardio-Oncology: A Comprehensive Review
Avirup Guha, Viraj Shah, Tarek Nahle, et al.
Current Cardiology Reports (2025) Vol. 27, Iss. 1
Closed Access
Mind the gap: unveiling the advantages and challenges of artificial intelligence in the healthcare ecosystem
Simona Curiello, Enrica Iannuzzi, Dirk Meissner, et al.
European Journal of Innovation Management (2025)
Closed Access
A Multi-Modal Unsupervised Machine Learning Approach for Biomedical Signal Processing during Cardiopulmonary Resuscitation
Saidul Islam, Jamal Bentahar, Robin Cohen, et al.
Information Sciences (2025), pp. 122114-122114
Open Access
Impact of human and artificial intelligence collaboration on workload reduction in medical image interpretation
Mingyang Chen, Yuting Wang, Qiankun Wang, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 4
Human-AI Teaming in the ICU: A Comparative Analysis of Data Scientists' and Clinicians’ Assessments on AI Augmentation and Automation at Work (Preprint)
Nadine Bienefeld, E. Keller, Gudela Grote
Journal of Medical Internet Research (2024) Vol. 26, pp. e50130-e50130
Open Access | Times Cited: 3
Challenges and Limitations of Human Oversight in Ethical AI Implementation in Healthcare: Balancing Digital Literacy and Professional Strain
Roanne van Voorst
Mayo Clinic Proceedings Digital Health (2024) Vol. 2, Iss. 4, pp. 559-563
Open Access | Times Cited: 3
Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties
Felix Busch, Lena Hoffmann, Daniel Truhn, et al.
BMC Medical Education (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 3
Explainable artificial intelligence in emergency medicine: an overview
Yohei Okada, Yilin Ning, Marcus Eng Hock Ong
Clinical and Experimental Emergency Medicine (2023) Vol. 10, Iss. 4, pp. 354-362
Open Access | Times Cited: 9
AI models in clinical neonatology: a review of modeling approaches and a consensus proposal for standardized reporting of model performance
Ameena Husain, Lindsey A. Knake, Brynne A. Sullivan, et al.
Pediatric Research (2024)
Closed Access | Times Cited: 2
Human-AI teaming: leveraging transactive memory and speaking up for enhanced team effectiveness
Nadine Bienefeld, Michaela Kolbe, Giovanni Camen, et al.
Frontiers in Psychology (2023) Vol. 14
Open Access | Times Cited: 7
Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach
Catherine J. Staes, Anna C. Beck, George Chalkidis, et al.
Journal of the American Medical Informatics Association (2023) Vol. 31, Iss. 1, pp. 174-187
Open Access | Times Cited: 7
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