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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:

The role of explainability in creating trustworthy artificial intelligence for health care: A comprehensive survey of the terminology, design choices, and evaluation strategies
Aniek F. Markus, Jan A. Kors, Peter R. Rijnbeek
Journal of Biomedical Informatics (2020) Vol. 113, pp. 103655-103655
Open Access | Times Cited: 474

Showing 1-25 of 474 citing articles:

Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics
Jianlong Zhou, Amir H. Gandomi, Fang Chen, et al.
Electronics (2021) Vol. 10, Iss. 5, pp. 593-593
Open Access | Times Cited: 405
A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion
A. S. Albahri, Ali M. Duhaim, Mohammed A. Fadhel, et al.
Information Fusion (2023) Vol. 96, pp. 156-191
Closed Access | Times Cited: 346
Explainable AI (XAI): A systematic meta-survey of current challenges and future opportunities
Waddah Saeed, Christian W. Omlin
Knowledge-Based Systems (2023) Vol. 263, pp. 110273-110273
Open Access | Times Cited: 335
From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
Meike Nauta, Jan Trienes, Shreyasi Pathak, et al.
ACM Computing Surveys (2023) Vol. 55, Iss. 13s, pp. 1-42
Open Access | Times Cited: 219
A Review of Taxonomies of Explainable Artificial Intelligence (XAI) Methods
Timo Speith
2022 ACM Conference on Fairness, Accountability, and Transparency (2022), pp. 2239-2250
Open Access | Times Cited: 181
Explainable, trustworthy, and ethical machine learning for healthcare: A survey
Khansa Rasheed, Adnan Qayyum, Mohammed Ghaly, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 106043-106043
Open Access | Times Cited: 178
Federated learning-based AI approaches in smart healthcare: concepts, taxonomies, challenges and open issues
Anichur Rahman, Md. Sazzad Hossain, Ghulam Muhammad, et al.
Cluster Computing (2022) Vol. 26, Iss. 4, pp. 2271-2311
Open Access | Times Cited: 166
Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Future
David Ahmedt‐Aristizabal, Mohammad Ali Armin, Simon Denman, et al.
Sensors (2021) Vol. 21, Iss. 14, pp. 4758-4758
Open Access | Times Cited: 157
Beware explanations from AI in health care
Boris Babic, Sara Gerke, Theodoros Evgeniou, et al.
Science (2021) Vol. 373, Iss. 6552, pp. 284-286
Closed Access | Times Cited: 149
Explainable Artificial Intelligence (XAI) 2.0: A manifesto of open challenges and interdisciplinary research directions
Luca Longo, Mario Brčić, Federico Cabitza, et al.
Information Fusion (2024) Vol. 106, pp. 102301-102301
Open Access | Times Cited: 135
Human-centered XAI: Developing design patterns for explanations of clinical decision support systems
Tjeerd Schoonderwoerd, Wiard Jorritsma, Mark A. Neerincx, et al.
International Journal of Human-Computer Studies (2021) Vol. 154, pp. 102684-102684
Open Access | Times Cited: 132
Explainable medical imaging AI needs human-centered design: guidelines and evidence from a systematic review
Haomin Chen, Catalina Gómez, Chien‐Ming Huang, et al.
npj Digital Medicine (2022) Vol. 5, Iss. 1
Open Access | Times Cited: 122
Survey of explainable artificial intelligence techniques for biomedical imaging with deep neural networks
Sajid Nazir, Diane M. Dickson, Muhammad Usman Akram
Computers in Biology and Medicine (2023) Vol. 156, pp. 106668-106668
Open Access | Times Cited: 117
To explain or not to explain?—Artificial intelligence explainability in clinical decision support systems
Julia Amann, Dennis Vetter, Stig Nikolaj Fasmer Blomberg, et al.
PLOS Digital Health (2022) Vol. 1, Iss. 2, pp. e0000016-e0000016
Open Access | Times Cited: 116
A manifesto on explainability for artificial intelligence in medicine
Carlo Combi, Beatrice Amico, Riccardo Bellazzi, et al.
Artificial Intelligence in Medicine (2022) Vol. 133, pp. 102423-102423
Open Access | Times Cited: 95
Application of explainable artificial intelligence in medical health: A systematic review of interpretability methods
Shahab S. Band, Atefeh Yarahmadi, Chung-Chian Hsu, et al.
Informatics in Medicine Unlocked (2023) Vol. 40, pp. 101286-101286
Open Access | Times Cited: 92
A Review of Trustworthy and Explainable Artificial Intelligence (XAI)
Vinay Chamola, Vikas Hassija, A. Razia Sulthana, et al.
IEEE Access (2023) Vol. 11, pp. 78994-79015
Open Access | Times Cited: 91
Explainable AI for clinical and remote health applications: a survey on tabular and time series data
Flavio Di Martino, Franca Delmastro
Artificial Intelligence Review (2022) Vol. 56, Iss. 6, pp. 5261-5315
Open Access | Times Cited: 85
Implementation of artificial intelligence techniques in microgrid control environment: Current progress and future scopes
Rohit Trivedi, Shafi Khadem
Energy and AI (2022) Vol. 8, pp. 100147-100147
Open Access | Times Cited: 84
A Review on Explainable Artificial Intelligence for Healthcare: Why, How, and When?
Subrato Bharati, M. Rubaiyat Hossain Mondal, Prajoy Podder
IEEE Transactions on Artificial Intelligence (2023) Vol. 5, Iss. 4, pp. 1429-1442
Open Access | Times Cited: 81
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction
Sunnie Kim, Elizabeth Anne Watkins, Olga Russakovsky, et al.
(2023), pp. 1-17
Open Access | Times Cited: 80
Harnessing the Power of AI: A Comprehensive Review of Its Impact and Challenges in Nursing Science and Healthcare
Seema Yelne, Minakshi Chaudhary, Karishma Dod, et al.
Cureus (2023)
Open Access | Times Cited: 73
Artificial Intelligence of Things for Smarter Healthcare: A Survey of Advancements, Challenges, and Opportunities
Stephanie Baker, Wei Xiang
IEEE Communications Surveys & Tutorials (2023) Vol. 25, Iss. 2, pp. 1261-1293
Open Access | Times Cited: 70
Ignore, Trust, or Negotiate: Understanding Clinician Acceptance of AI-Based Treatment Recommendations in Health Care
Venkatesh Sivaraman, Leigh A. Bukowski, Joel Levin, et al.
(2023), pp. 1-18
Open Access | Times Cited: 51
Artificial intelligence in future nursing care: Exploring perspectives of nursing professionals - A descriptive qualitative study
Moustaq Karim Khan Rony, Ibne Kayesh, Shuvashish Das Bala, et al.
Heliyon (2024) Vol. 10, Iss. 4, pp. e25718-e25718
Open Access | Times Cited: 49
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