Improving Informed Consent Models for Endobronchial Ultrasound With Artificial Intelligence
AI-generated materials improve accessibility in the IC for EBUS. While human supervision remains essential, future studies could strengthen the integration of AI-assisted and video-based consent tools in clinical practice.
Authors
- Ana Oliveira (ORCID: https://orcid.org/0000-0001-7893-7520)
- Sara Ferreira
- Gabriela Fernandes (ORCID: https://orcid.org/0000-0002-3549-0770)
- Catarina Sousa (ORCID: https://orcid.org/0000-0002-8231-1608)
- Ana Aguiar (ORCID: https://orcid.org/0000-0001-7643-8963)
- Hélder Novais Bastos (ORCID: https://orcid.org/0000-0002-1412-4202)
- Cláudia Freitas (ORCID: https://orcid.org/0000-0001-6807-8558)
- André Terras
- Diana Moreira‐Sousa (ORCID: https://orcid.org/0000-0003-4514-6110)
- Maria Jacob (ORCID: https://orcid.org/0000-0001-9751-7636)
- Adriana Magalhães
- Francisco Pereira Machado
- Filipa Furtado
Institutions
- Universidade do Porto (PT)
- Hospital Center of Cova da Beira (PT)
- Administração Regional de Saúde de Lisboa e Vale do Tejo (PT)
- Instituto de Saúde (BR)
- Institute of Biomedical Science (GB)
Publication Details
- Journal
- Journal of Bronchology & Interventional Pulmonology
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1097/lbr.0000000000001044
- Primary Topic
- Tracheal and airway disorders
- Type
- article
- Field-Weighted Citation Impact
- 0.00