ArticleBMJ open2023
What is the future of artificial intelligence in obstetrics? A qualitative study among healthcare professionals.
Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Improving Explainability and Integrability of Medical AI to Promote Health Care Professional Acceptance and Use: Mixed Systematic Review.Journal of medical Internet research · 2025Pooled it
- Healthcare professionals' perspectives on artificial intelligence in patient care: a systematic review of hindering and facilitating factors on different levels.BMC health services research · 2025Pooled it
- The Perceived Influence of AI on the Craftsmanship of Physicians: Qualitative Interview and Focus Group Study.JMIR AI · 2026Article
- Artificial Intelligence as an Add-On Instrument in Fetal Ultrasound; Sonographers' and Obstetricians' Expectations.Prenatal diagnosis · 2026Article
- The potential, perils and pitfalls of Artificial intelligence (AI) in Assisted Reproductive Technologies (ART).Reproductive biology and endocrinology : RB&E · 2026Review
- Healthcare professionals' perspectives on artificial intelligence in clinical practice: a systematic review of facilitators and challenges.Oxford open digital health · 2026Article
- Digital therapeutics into geriatric cardiovascular emergency care.Frontiers in digital health · 2026Review
- Artificial intelligence-driven clinical guideline recommendations in maternal care: How trustworthy are they?Biomedica : revista del Instituto Nacional de Salud · 2025Article
- Exploring trust factors in AI-healthcare integration: a rapid review.Frontiers in artificial intelligence · 2025Review
- Machine learning-based prediction models in medical decision-making in kidney disease: patient, caregiver, and clinician perspectives on trust and appropriate use.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Application of ultrasound in combination with other methods in gynecological disease: artificial intelligence, surgery, and drugs.Frontiers in oncology · 2025Review
- Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review.Journal of clinical medicine · 2024Review
- Searching for Value Sensitive Design in Applied Health AI: A Narrative Review.Yearbook of medical informatics · 2024Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis work explores the perceptions of obstetrical clinicians about artificial intelligence (AI) in order to bridge the gap in uptake of AI between research and medical practice. Identifying potential areas where AI can contribute to clinical practice, enables AI research to align with the needs of clinicians and ultimately patients.
designQualitative interview study.
settingA national study conducted in the Netherlands between November 2022 and February 2023.
participantsDutch clinicians working in obstetrics with varying relevant work experience, gender and age. ANALYSIS: Thematic analysis of qualitative interview transcripts.
resultsThirteen gynaecologists were interviewed about hypothetical scenarios of an implemented AI model. Thematic analysis identified two major themes: perceived usefulness and trust. Usefulness involved AI extending human brain capacity in complex pattern recognition and information processing, reducing contextual influence and saving time. Trust required validation, explainability and successful personal experience. This result shows two paradoxes: first, AI is expected to provide added value by surpassing human capabilities, yet also a need to understand the parameters and their influence on predictions for trust and adoption was expressed. Second, participants recognised the value of incorporating numerous parameters into a model, but they also believed that certain contextual factors should only be considered by humans, as it would be undesirable for AI models to use that information.
conclusionsObstetricians' opinions on the potential value of AI highlight the need for clinician-AI researcher collaboration. Trust can be built through conventional means like randomised controlled trials and guidelines. Holistic impact metrics, such as changes in workflow, not just clinical outcomes, should guide AI model development. Further research is needed for evaluating evolving AI systems beyond traditional validation methods.
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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.