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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 false hope of current approaches to explainable artificial intelligence in health care
Marzyeh Ghassemi, Luke Oakden‐Rayner, Andrew L. Beam
The Lancet Digital Health (2021) Vol. 3, Iss. 11, pp. e745-e750
Open Access | Times Cited: 724

Showing 1-25 of 724 citing articles:

Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Sajid Ali, Tamer Abuhmed, Shaker El–Sappagh, et al.
Information Fusion (2023) Vol. 99, pp. 101805-101805
Open Access | Times Cited: 608
Artificial intelligence for multimodal data integration in oncology
Jana Lipková, Richard J. Chen, Bowen Chen, et al.
Cancer Cell (2022) Vol. 40, Iss. 10, pp. 1095-1110
Open Access | Times Cited: 312
Survey of Explainable AI Techniques in Healthcare
Ahmad Chaddad, Jihao Peng, Jian Xu, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 634-634
Open Access | Times Cited: 258
Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Baptiste Vasey, Myura Nagendran, Bruce Campbell, et al.
Nature Medicine (2022) Vol. 28, Iss. 5, pp. 924-933
Open Access | Times Cited: 247
Artificial intelligence in histopathology: enhancing cancer research and clinical oncology
Artem Shmatko, Narmin Ghaffari Laleh, Moritz Gerstung, et al.
Nature Cancer (2022) Vol. 3, Iss. 9, pp. 1026-1038
Closed Access | Times Cited: 245
Six Human-Centered Artificial Intelligence Grand Challenges
Özlem Özmen Garibay, Brent Winslow, Salvatore Andolina, et al.
International Journal of Human-Computer Interaction (2023) Vol. 39, Iss. 3, pp. 391-437
Open Access | Times Cited: 200
Algorithmic fairness in artificial intelligence for medicine and healthcare
Richard J. Chen, Judy J. Wang, Drew F. K. Williamson, et al.
Nature Biomedical Engineering (2023) Vol. 7, Iss. 6, pp. 719-742
Open Access | Times Cited: 189
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
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI
Baptiste Vasey, Myura Nagendran, Bruce Campbell, et al.
BMJ (2022), pp. e070904-e070904
Open Access | Times Cited: 162
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
Explainability and artificial intelligence in medicine
Sandeep Reddy
The Lancet Digital Health (2022) Vol. 4, Iss. 4, pp. e214-e215
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
Transparency of AI in Healthcare as a Multilayered System of Accountabilities: Between Legal Requirements and Technical Limitations
Anastasiya Kiseleva, Dimitris Kotzinos, Paul De Hert
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 108
Benchmarking saliency methods for chest X-ray interpretation
Adriel Saporta, Xiaotong Gui, Ashwin Agrawal, et al.
Nature Machine Intelligence (2022) Vol. 4, Iss. 10, pp. 867-878
Open Access | Times Cited: 107
Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review
Arsela Prelaj, Vanja Mišković, Michele Zanitti, et al.
Annals of Oncology (2023) Vol. 35, Iss. 1, pp. 29-65
Open Access | Times Cited: 97
Computational approaches to Explainable Artificial Intelligence: Advances in theory, applications and trends
J. M. Górriz, I. Álvarez, Agustín Álvarez-Marquina, et al.
Information Fusion (2023) Vol. 100, pp. 101945-101945
Open Access | Times Cited: 96
Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease
Maarten van Smeden, Georg Heinze, Ben Van Calster, et al.
European Heart Journal (2022) Vol. 43, Iss. 31, pp. 2921-2930
Open Access | Times Cited: 95
Experimental evidence of effective human–AI collaboration in medical decision-making
Carlo Reverberi, Tommaso Rigon, Aldo Solari, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 94
Explainable artificial intelligence for mental health through transparency and interpretability for understandability
Dan W. Joyce, Andrey Kormilitzin, Katharine Smith, et al.
npj Digital Medicine (2023) Vol. 6, Iss. 1
Open Access | Times Cited: 93
Explainable artificial intelligence in skin cancer recognition: A systematic review
Katja Hauser, Alexander Kurz, Sarah Haggenmüller, et al.
European Journal of Cancer (2022) Vol. 167, pp. 54-69
Open Access | Times Cited: 91
Computer vision and machine learning for medical image analysis: recent advances, challenges, and way forward
Eyad Elyan, Pattaramon Vuttipittayamongkol, Pamela Johnston, et al.
Artificial Intelligence Surgery (2022)
Open Access | Times Cited: 89
Effects of Explainable Artificial Intelligence on trust and human behavior in a high-risk decision task
Benedikt Leichtmann, Christina Humer, Andreas Hinterreiter, et al.
Computers in Human Behavior (2022) Vol. 139, pp. 107539-107539
Open Access | Times Cited: 74
Fast and scalable search of whole-slide images via self-supervised deep learning
Chengkuan Chen, Ming Lu, Drew F. K. Williamson, et al.
Nature Biomedical Engineering (2022) Vol. 6, Iss. 12, pp. 1420-1434
Open Access | Times Cited: 69
Interpretable and explainable machine learning: A methods‐centric overview with concrete examples
Ričards Marcinkevičs, Julia E. Vogt
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2023) Vol. 13, Iss. 3
Open Access | Times Cited: 68
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