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Accès ouvert déclaré 2026 article

Mapping patients’ and professionals’ perceptions of artificial intelligence in radiotherapy: a scoping review

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Background Artificial intelligence (AI) is increasingly integrated into radiotherapy workflows. Evidence on patients' and professionals' attitudes toward AI in radiotherapy remains limited and fragmented. Objectives To summarize the current evidence on patients and professionals' attitudes toward AI in radiotherapy, identify knowledge gaps, and highlight priorities for future research. Methods Studies including adult cancer patients receiving radiotherapy and/or radiotherapy professionals, reporting attitudes toward AI in radiotherapy were eligible for inclusion. The sources of evidence PubMed, MEDLINE, EMBASE, and CINAHL were searched on September 11, 2025. Two reviewers independently screened the studies. Data were extracted using a standardized form. Studies were categorized post hoc as positive, cautiously positive, cautiously negative, or negative based on overall orientation, and themes were identified inductively. The review followed PRISMA-ScR guidelines. Results 1901 studies were identified, and nineteen studies were included in the review. Most studies were cross-sectional surveys. Patients generally accepted AI when framed as supportive, but emphasized trust, transparency, and the desire to be informed when AI is being used. One study reported more skeptical patient views. Radiotherapy professionals were generally cautiously positive, seeing benefits for efficiency, consistency, and quality, but expressed concerns about deskilling, training gaps, governance, and accountability. Conclusions Attitudes toward AI in radiotherapy are predominantly cautiously positive but conditional on transparency, human oversight, adequate training, and robust governance. Addressing educational, organizational, and human factors alongside technical development is essential for safe and sustainable AI implementation in radiotherapy. Future research should prioritize longitudinal, qualitative, and implementation-focused studies.

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DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Mapping patients’ and professionals’ perceptions of artificial intelligence in radiotherapy: a scoping review
Date Crossref
01/12/2026
Éditeur
Elsevier BV
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude et ne compte pas comme une seconde source scientifique indépendante.

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Sujets associés

Artificial Intelligence in Healthcare and EducationAdvanced Radiotherapy TechniquesRadiomics and Machine Learning in Medical Imaging

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