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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:

Re-focusing explainability in medicine
Laura Arbelaez Ossa, Georg Starke, Giorgia Lorenzini, et al.
Digital Health (2022) Vol. 8, pp. 205520762210744-205520762210744
Open Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

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
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: 46
Designing interpretable ML system to enhance trust in healthcare: A systematic review to proposed responsible clinician-AI-collaboration framework
Elham Nasarian, Roohallah Alizadehsani, U. Rajendra Acharya, et al.
Information Fusion (2024) Vol. 108, pp. 102412-102412
Open Access | Times Cited: 21
Finding Consensus on Trust in AI in Health Care: Recommendations From a Panel of International Experts
Georg Starke, Felix Gille, Alberto Termine, et al.
Journal of Medical Internet Research (2025) Vol. 27, pp. e56306-e56306
Open Access | Times Cited: 1
Assessment of Performance, Interpretability, and Explainability in Artificial Intelligence–Based Health Technologies: What Healthcare Stakeholders Need to Know
Line Farah, Juliette Murris, Isabelle Borget, et al.
Mayo Clinic Proceedings Digital Health (2023) Vol. 1, Iss. 2, pp. 120-138
Closed Access | Times Cited: 34
Machine-learning versus traditional approaches for atherosclerotic cardiovascular risk prognostication in primary prevention cohorts: a systematic review and meta-analysis
Weber Liu, Liliana Laranjo, Harry Klimis, et al.
European Heart Journal - Quality of Care and Clinical Outcomes (2023)
Open Access | Times Cited: 31
Exploring Artificial Intelligence in Anesthesia: A Primer on Ethics, and Clinical Applications
Marco Cascella, Maura Tracey, Emiliano Petrucci, et al.
Surgeries (2023) Vol. 4, Iss. 2, pp. 264-274
Open Access | Times Cited: 27
Trust and acceptability of data-driven clinical recommendations in everyday practice: A scoping review
Ruth Evans, Louise Bryant, Gregor Russell, et al.
International Journal of Medical Informatics (2024) Vol. 183, pp. 105342-105342
Open Access | Times Cited: 8
Embryologist agreement when assessing blastocyst implantation probability: is data-driven prediction the solution to embryo assessment subjectivity?
Daniel E. Fordham, Dror Rosentraub, Avital Polsky, et al.
Human Reproduction (2022) Vol. 37, Iss. 10, pp. 2275-2290
Closed Access | Times Cited: 32
Ebenen der Explizierbarkeit für medizinische künstliche Intelligenz: Was brauchen wir normativ und was können wir technisch erreichen?
Frank Ursin, Felix Lindner, Timo Ropinski, et al.
Ethik in der Medizin (2023) Vol. 35, Iss. 2, pp. 173-199
Open Access | Times Cited: 16
Machine learning to predict antimicrobial resistance: future applications in clinical practice?
Yousra Kherabi, Michaël Thy, Donia Bouzid, et al.
Infectious Diseases Now (2024) Vol. 54, Iss. 3, pp. 104864-104864
Closed Access | Times Cited: 6
Harnessing AI for enhanced evidence-based laboratory medicine (EBLM)
Tahir S. Pillay, Deniz İlhan Topçu, Sedef Yenice
Clinica Chimica Acta (2025) Vol. 569, pp. 120181-120181
Open Access
Research ethics for AI in healthcare: how, when and who
Francesc Pifarré-Esquerda, Montse Esquerda, Francesc García Cuyàs
AI & Society (2025)
Closed Access
PON-P3: Accurate Prediction of Pathogenicity of Amino Acid Substitutions
Muhammad Kabir, Saeed Ahmed, Haoyang Zhang, et al.
International Journal of Molecular Sciences (2025) Vol. 26, Iss. 5, pp. 2004-2004
Open Access
Cell Maps for Artificial Intelligence: AI-Ready Maps of Human Cell Architecture from Disease-Relevant Cell Lines
Tim W. Clark, Jillian Mohan, Leah V. Schaffer, et al.
bioRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 5
Inteligencia artificial en medicina: aspectos éticos, deontológicos y el impacto en la relación médico-paciente
Montse Esquerda, Francesc Pifarré-Esquerda
Medicina Clínica (2024) Vol. 163, Iss. 3, pp. e44-e48
Closed Access | Times Cited: 4
Predicting Atrial Fibrillation Relapse Using Bayesian Networks: Explainable AI Approach
João Miguel Alves, Daniel Matos, Tiago Silva Martins, et al.
JMIR Cardio (2025) Vol. 9, pp. e59380-e59380
Open Access
When and what patients need to know about AI in clinical care
David Shaw, Giorgia Lorenzini, Laura Arbelaez Ossa, et al.
Schweizerische medizinische Wochenschrift (2025) Vol. 155, Iss. 1, pp. 4013-4013
Open Access
CXAI: Explaining Convolutional Neural Networks for Medical Imaging Diagnostic
Zakaria Rguibi, Abdelmajid Hajami, Dya Zitouni, et al.
Electronics (2022) Vol. 11, Iss. 11, pp. 1775-1775
Open Access | Times Cited: 19
Clinician's guide to trustworthy and responsible artificial intelligence in cardiovascular imaging
Liliána Szabó, Zahra Raisi‐Estabragh, Ahmed Salih, et al.
Frontiers in Cardiovascular Medicine (2022) Vol. 9
Open Access | Times Cited: 19
Artificial intelligence predictive analytics in heart failure: results of the pilot phase of a pragmatic randomized clinical trial
Konstantinos Sideris, Charlene Weir, Carsten Schmalfuss, et al.
Journal of the American Medical Informatics Association (2024) Vol. 31, Iss. 4, pp. 919-928
Open Access | Times Cited: 3
Artificial intelligence model for tumoral clinical decision support systems
Guillermo Iglesias, Edgar Talavera, Jesús Troya, et al.
Computer Methods and Programs in Biomedicine (2024) Vol. 253, pp. 108228-108228
Open Access | Times Cited: 3
The ethical requirement of explainability for AI-DSS in healthcare: a systematic review of reasons
Nils Freyer, Dominik Groß, Myriam Lipprandt
BMC Medical Ethics (2024) Vol. 25, Iss. 1
Open Access | Times Cited: 3
User-Centric Explainability in Healthcare: A Knowledge-Level Perspective of Informed Machine Learning
Luis Oberste, Armin Heinzl
IEEE Transactions on Artificial Intelligence (2022) Vol. 4, Iss. 4, pp. 840-857
Closed Access | Times Cited: 15
A Theoretical Framework for AI Models Explainability with Application in Biomedicine
Matteo Rizzo, Alberto Veneri, Andrea Albarelli, et al.
(2023), pp. 1-9
Open Access | Times Cited: 8
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