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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:

A comparison of deep learning performance against health-care professionals in detecting diseases from medical imaging: a systematic review and meta-analysis
Xiaoxuan Liu, Livia Faes, Aditya U. Kale, et al.
The Lancet Digital Health (2019) Vol. 1, Iss. 6, pp. e271-e297
Open Access | Times Cited: 1386

Showing 26-50 of 1386 citing articles:

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
AI-based computer-aided diagnosis (AI-CAD): the latest review to read first
Hiroshi Fujita
Radiological Physics and Technology (2020) Vol. 13, Iss. 1, pp. 6-19
Closed Access | Times Cited: 246
Role of Artificial Intelligence in Patient Safety Outcomes: Systematic Literature Review
Avishek Choudhury, Onur Asan
JMIR Medical Informatics (2020) Vol. 8, Iss. 7, pp. e18599-e18599
Open Access | Times Cited: 245
A global review of publicly available datasets for ophthalmological imaging: barriers to access, usability, and generalisability
Saad Khan, Xiaoxuan Liu, Siddharth Nath, et al.
The Lancet Digital Health (2020) Vol. 3, Iss. 1, pp. e51-e66
Open Access | Times Cited: 245
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI extension
Samantha Cruz Rivera, Xiaoxuan Liu, An‐Wen Chan, et al.
The Lancet Digital Health (2020) Vol. 2, Iss. 10, pp. e549-e560
Open Access | Times Cited: 239
Risk of bias in studies on prediction models developed using supervised machine learning techniques: systematic review
Constanza L. Andaur Navarro, Johanna AAG Damen, Toshihiko Takada, et al.
BMJ (2021), pp. n2281-n2281
Open Access | Times Cited: 239
Artificial intelligence in medical imaging: switching from radiographic pathological data to clinically meaningful endpoints
Ohad Oren, Bernard J. Gersh, Deepak L. Bhatt
The Lancet Digital Health (2020) Vol. 2, Iss. 9, pp. e486-e488
Open Access | Times Cited: 238
Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension
Xiaoxuan Liu, Samantha Cruz Rivera, David Moher, et al.
The Lancet Digital Health (2020) Vol. 2, Iss. 10, pp. e537-e548
Open Access | Times Cited: 214
Guidelines for clinical trial protocols for interventions involving artificial intelligence: the SPIRIT-AI Extension
Samantha Cruz Rivera, Xiaoxuan Liu, An‐Wen Chan, et al.
BMJ (2020), pp. m3210-m3210
Open Access | Times Cited: 214
Medical imaging and nuclear medicine: a Lancet Oncology Commission
Hedvig Hricak, May Abdel‐Wahab, Rifat Atun, et al.
The Lancet Oncology (2021) Vol. 22, Iss. 4, pp. e136-e172
Open Access | Times Cited: 211
The need to separate the wheat from the chaff in medical informatics
Federico Cabitza, Andrea Campagner
International Journal of Medical Informatics (2021) Vol. 153, pp. 104510-104510
Open Access | Times Cited: 204
Time to reality check the promises of machine learning-powered precision medicine
Jack Wilkinson, Kellyn F Arnold, Eleanor J. Murray, et al.
The Lancet Digital Health (2020) Vol. 2, Iss. 12, pp. e677-e680
Open Access | Times Cited: 195
Deep learning for biomedical photoacoustic imaging: A review
Janek Gröhl, Melanie Schellenberg, Kris K. Dreher, et al.
Photoacoustics (2021) Vol. 22, pp. 100241-100241
Open Access | Times Cited: 190
Insights into Systemic Disease through Retinal Imaging-Based Oculomics
Siegfried Wagner, Dun Jack Fu, Livia Faes, et al.
Translational Vision Science & Technology (2020) Vol. 9, Iss. 2, pp. 6-6
Open Access | Times Cited: 187
Artificial Intelligence and Patient-Centered Decision-Making
Jens Christian Bjerring, Jacob Busch
Philosophy & Technology (2020) Vol. 34, Iss. 2, pp. 349-371
Closed Access | Times Cited: 177
Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications
Mostafa Rahimi Azghadi, Corey Lammie, Jason K. Eshraghian, et al.
IEEE Transactions on Biomedical Circuits and Systems (2020) Vol. 14, Iss. 6, pp. 1138-1159
Open Access | Times Cited: 174
Medical deep learning—A systematic meta-review
Jan Egger, Christina Gsaxner, Antonio Pepe, et al.
Computer Methods and Programs in Biomedicine (2022) Vol. 221, pp. 106874-106874
Open Access | Times Cited: 172
Artificial Intelligence in Dermatology: A Primer
Albert T. Young, Mulin Xiong, Jacob Pfau, et al.
Journal of Investigative Dermatology (2020) Vol. 140, Iss. 8, pp. 1504-1512
Open Access | Times Cited: 169
Artificial intelligence and machine learning algorithms for early detection of skin cancer in community and primary care settings: a systematic review
O. T. G. Jones, Rubeta Matin, Mihaela van der Schaar, et al.
The Lancet Digital Health (2022) Vol. 4, Iss. 6, pp. e466-e476
Open Access | Times Cited: 169
Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology
Lior Drukker, J. Alison Noble, Aris T. Papageorghiou
Ultrasound in Obstetrics and Gynecology (2020) Vol. 56, Iss. 4, pp. 498-505
Open Access | Times Cited: 165
Artificial intelligence in cancer research, diagnosis and therapy
Olivier Elemento, Christina Leslie, Johan Lundin, et al.
Nature reviews. Cancer (2021) Vol. 21, Iss. 12, pp. 747-752
Open Access | Times Cited: 164
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
An international survey on AI in radiology in 1,041 radiologists and radiology residents part 1: fear of replacement, knowledge, and attitude
Merel Huisman, Erik Ranschaert, William Parker, et al.
European Radiology (2021) Vol. 31, Iss. 9, pp. 7058-7066
Open Access | Times Cited: 158
Candidate biomarkers in psychiatric disorders: state of the field
Anissa Abi‐Dargham, Scott J. Moeller, Farzana Ali, et al.
World Psychiatry (2023) Vol. 22, Iss. 2, pp. 236-262
Open Access | Times Cited: 156
Limits of trust in medical AI
Joshua Hatherley
Journal of Medical Ethics (2020) Vol. 46, Iss. 7, pp. 478-481
Closed Access | Times Cited: 155

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