ArticleJournal of translational medicine2020
Perceptions of artificial intelligence in healthcare: findings from a qualitative survey study among actors in France.
Article in Journal of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 126 papers, 2 of them syntheses that pooled it.
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Who cites it
126 citing papers in PubMed, 2 syntheses or guidelines pooled it, 289 citations in OpenAlex.
- Stakeholder Perspectives of Clinical Artificial Intelligence Implementation: Systematic Review of Qualitative Evidence.Journal of medical Internet research · 2023Pooled it
- Efficacy and pitfalls of digital technologies in healthcare services: A systematic review of two decades.Frontiers in public health · 2022Pooled it
- Primary Care Doctors' Perspectives and Experiences With a Chest X-Ray AI Triage Program: Qualitative Study.Journal of medical Internet research · 2026Article
- Physicians' perspectives on artificial intelligence in electrocardiography in clinical practice: a qualitative study.BMC medical ethics · 2026Article
- Factors Influencing Nursing Internship Students' Readiness to Use AI: Cross-Sectional Study Using Neural Network Analysis.JMIR nursing · 2026Article
- Artificial Intelligence Adoption in Public Health Practice: A Cross-Sectional Study of Practical Determinants Among Healthcare Professionals.Healthcare (Basel, Switzerland) · 2026Article
- Use, Concerns, and Perspectives on AI in Health Care Among French Health Professionals and Students: Web-Based Cross-Sectional Survey.JMIR medical education · 2026Article
- Ethical and Governance Challenges of AI in Medical Imaging and Diagnostics: A Systematic Survey and Policy Framework Recommendations.Healthcare (Basel, Switzerland) · 2026Review
- Constructs Influencing Patient Perceptions of Use of AI in Medical Imaging Analysis: Systematic Review.Interactive journal of medical research · 2026Review
- AI and clinicians growing together: A cross-sectional survey of clinicians' attitudes toward AI-CDSS with comparison to 2020 data.Clinical medicine (London, England) · 2026Article
- Article
- Catching pancreatic cancer early: Are we there yet?Journal of the National Cancer Center · 2026Review
- Expectations and concerns of primary healthcare patients in rural areas and small towns in Poland regarding artificial intelligence.Scientific reports · 2026Article
- Stakeholders' Perceived Benefits and Concerns Regarding Artificial Intelligence in the Care of Older Adults.Journal of the American Geriatrics Society · 2026Article
- AI-Enhanced Qualitative Analysis in Healthcare: Unlocking Insight from Interviews of Leadership at Top-Performing Academic Medical Centers.Healthcare (Basel, Switzerland) · 2026Article
- Parents' Perspectives on Artificial Intelligence-Supported Pediatric Healthcare Services: A Descriptive and Correlational Study.Journal of nursing management · 2026Article
- Perception of artificial intelligence and machine learning applications in the Nigerian healthcare sector: A cross-sectional study.PLOS global public health · 2026Article
- Perspectives on healthcare artificial intelligence policy from health equity professionals: findings from an interview study.Frontiers in digital health · 2026Article
- Healthcare professionals' perspectives on artificial intelligence in clinical practice: a systematic review of facilitators and challenges.Oxford open digital health · 2026Article
- Artificial intelligence applications in oxaliplatin-based chemotherapy for colon cancer: advancing prognosis, toxicity prediction, and dose personalization.Frontiers in pharmacology · 2026Review
66 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI), with its seemingly limitless power, holds the promise to truly revolutionize patient healthcare. However, the discourse carried out in public does not always correlate with the actual impact. Thus, we aimed to obtain both an overview of how French health professionals perceive the arrival of AI in daily practice and the perception of the other actors involved in AI to have an overall understanding of this issue.
methodsForty French stakeholders with diverse backgrounds were interviewed in Paris between October 2017 and June 2018 and their contributions analyzed using the grounded theory method (GTM).
resultsThe interviews showed that the various actors involved all see AI as a myth to be debunked. However, their views differed. French healthcare professionals, who are strategically placed in the adoption of AI tools, were focused on providing the best and safest care for their patients. Contrary to popular belief, they are not always seeing the use of these tools in their practice. For healthcare industrial partners, AI is a true breakthrough but legal difficulties to access individual health data could hamper its development. Institutional players are aware that they will have to play a significant role concerning the regulation of the use of these tools. From an external point of view, individuals without a conflict of interest have significant concerns about the sustainability of the balance between health, social justice, and freedom. Health researchers specialized in AI have a more pragmatic point of view and hope for a better transition from research to practice.
conclusionAlthough some hyperbole has taken over the discourse on AI in healthcare, diverse opinions and points of view have emerged among French stakeholders. The development of AI tools in healthcare will be satisfactory for everyone only by initiating a collaborative effort between all those involved. It is thus time to also consider the opinion of patients and, together, address the remaining questions, such as that of responsibility.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.