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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:

Artificial intelligence in healthcare
Kun‐Hsing Yu, Andrew L. Beam, Isaac S. Kohane
Nature Biomedical Engineering (2018) Vol. 2, Iss. 10, pp. 719-731
Closed Access | Times Cited: 2026

Showing 1-25 of 2026 citing articles:

High-performance medicine: the convergence of human and artificial intelligence
Eric J. Topol
Nature Medicine (2018) Vol. 25, Iss. 1, pp. 44-56
Closed Access | Times Cited: 4765
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.
arXiv (Cornell University) (2021)
Open Access | Times Cited: 1524
Resistance to Medical Artificial Intelligence
Chiara Longoni, Andrea Bonezzi, Carey K. Morewedge
Journal of Consumer Research (2019) Vol. 46, Iss. 4, pp. 629-650
Closed Access | Times Cited: 1071
Revolutionizing healthcare: the role of artificial intelligence in clinical practice
Shuroug A. Alowais, Sahar S. Alghamdi, Nada Alsuhebany, et al.
BMC Medical Education (2023) Vol. 23, Iss. 1
Open Access | Times Cited: 1018
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
Artificial Intelligence and Machine Learning in Clinical Medicine, 2023
Charlotte Haug, Jeffrey M. Drazen
New England Journal of Medicine (2023) Vol. 388, Iss. 13, pp. 1201-1208
Closed Access | Times Cited: 647
Deep learning in histopathology: the path to the clinic
Jeroen van der Laak, Geert Litjens, Francesco Ciompi
Nature Medicine (2021) Vol. 27, Iss. 5, pp. 775-784
Open Access | Times Cited: 599
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction
Laila Rasmy, Yang Xiang, Ziqian Xie, et al.
npj Digital Medicine (2021) Vol. 4, Iss. 1
Open Access | Times Cited: 538
Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence
Gary S. Collins, Paula Dhiman, Constanza L. Andaur Navarro, et al.
BMJ Open (2021) Vol. 11, Iss. 7, pp. e048008-e048008
Open Access | Times Cited: 533
ClinicalBERT: Modeling Clinical Notes and Predicting Hospital Readmission
Kexin Huang, Jaan Altosaar, Rajesh Ranganath
arXiv (Cornell University) (2019)
Open Access | Times Cited: 518
Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond
Guang Yang, Qinghao Ye, Jun Xia
Information Fusion (2021) Vol. 77, pp. 29-52
Open Access | Times Cited: 513
Ethical and legal challenges of artificial intelligence-driven healthcare
Sara Gerke, Timo Minssen, Glenn Cohen
Elsevier eBooks (2020), pp. 295-336
Open Access | Times Cited: 504
A comprehensive AI policy education framework for university teaching and learning
Cecilia Ka Yuk Chan
International Journal of Educational Technology in Higher Education (2023) Vol. 20, Iss. 1
Open Access | Times Cited: 487
Machine learning for the prediction of sepsis: a systematic review and meta-analysis of diagnostic test accuracy
Lucas M. Fleuren, Thomas Klausch, Charlotte Zwager, et al.
Intensive Care Medicine (2020) Vol. 46, Iss. 3, pp. 383-400
Open Access | Times Cited: 486
The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
Melissa Haendel, Christopher G. Chute, Tellen D. Bennett, et al.
Journal of the American Medical Informatics Association (2020) Vol. 28, Iss. 3, pp. 427-443
Open Access | Times Cited: 457
Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015–20): a comparative analysis
Urs J. Muehlematter, Paola Daniore, Kerstin Noëlle Vokinger
The Lancet Digital Health (2021) Vol. 3, Iss. 3, pp. e195-e203
Open Access | Times Cited: 439
Improving the accuracy of medical diagnosis with causal machine learning
Jonathan G. Richens, Ciarán M. Lee, Saurabh Johri
Nature Communications (2020) Vol. 11, Iss. 1
Open Access | Times Cited: 438
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases
Monika A. Myszczynska, Poojitha N. Ojamies, Alix M.B. Lacoste, et al.
Nature Reviews Neurology (2020) Vol. 16, Iss. 8, pp. 440-456
Closed Access | Times Cited: 435
Artificial Intelligence in Healthcare: Review and Prediction Case Studies
Guoguang Rong, Arnaldo Mendez, Elie Bou Assi, et al.
Engineering (2020) Vol. 6, Iss. 3, pp. 291-301
Open Access | Times Cited: 420
Application of explainable artificial intelligence for healthcare: A systematic review of the last decade (2011–2022)
Hui Wen Loh, Chui Ping Ooi, Silvia Seoni, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 226, pp. 107161-107161
Open Access | Times Cited: 419
Introducing Artificial Intelligence Training in Medical Education
Ketan Paranjape, Michiel Schinkel, Rishi Panday, et al.
JMIR Medical Education (2019) Vol. 5, Iss. 2, pp. e16048-e16048
Open Access | Times Cited: 418
Global Evolution of Research in Artificial Intelligence in Health and Medicine: A Bibliometric Study
Bach Xuan Tran, Giang Thu Vu, Giang Hai Ha, et al.
Journal of Clinical Medicine (2019) Vol. 8, Iss. 3, pp. 360-360
Open Access | Times Cited: 358
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
A review of mathematical modeling, artificial intelligence and datasets used in the study, prediction and management of COVID-19
Youssoufa Mohamadou, Aminou Halidou, Pascalin Tiam Kapen
Applied Intelligence (2020) Vol. 50, Iss. 11, pp. 3913-3925
Open Access | Times Cited: 322
Quo vadis artificial intelligence?
Yuchen Jiang, Xiang Li, Hao Luo, et al.
Discover Artificial Intelligence (2022) Vol. 2, Iss. 1
Open Access | Times Cited: 307
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