FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Lekadir, K. 
ORCID: 0000-0002-9456-1612, Frangi, A. F., Porras, A. R. , Glocker, B., Cintas, C., Langlotz, C. P., Weicken, E., Asselbergs, F. W., Prior, F., Collins, G. S., Kaissis, G., Tsakou, G., Buvat, I., Kalpathy-Cramer, J., Mongan, J., Schnabel, J. A., Kushibar, K., Riklund, K., Marias, K., Amugongo, L. M., Fromont, L. A., Maier-Hein, L., Cerdá-Alberich, L., Martí-Bonmatí, L., Cardoso, M. J., Bobowicz, M., Shabani, M., Tsiknakis, M., Zuluaga, M. A., Fritzsche, M-C., Camacho, M., Linguraru, M. G., Wenzel, M., De Bruijne, M., Tolsgaard, M. G., Goisauf, M., Cano Abadía, M., Papanikolaou, N., Lazrak, N., Pujol, O., Osuala, R., Napel, S., Colantonio, S., Joshi, S., Klein, S., Aussó, S., Rogers, W. A., Salahuddin, Z., Starmans, M. P. A., FUTURE-AI Consortium & Botwe, B. O. ORCID: 0000-0002-0477-640X (2025).
FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.
BMJ, 388,
article number e081554.
doi: 10.1136/bmj-2024-081554
Abstract
Despite major advances in artificial intelligence (AI) research for healthcare, the deployment and adoption of AI technologies remain limited in clinical practice. This paper describes the FUTURE-AI framework, which provides guidance for the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI Consortium was founded in 2021 and comprises 117 interdisciplinary experts from 50 countries representing all continents, including AI scientists, clinical researchers, biomedical ethicists, and social scientists. Over a two year period, the FUTURE-AI guideline was established through consensus based on six guiding principles—fairness, universality, traceability, usability, robustness, and explainability. To operationalise trustworthy AI in healthcare, a set of 30 best practices were defined, addressing technical, clinical, socioethical, and legal dimensions. The recommendations cover the entire lifecycle of healthcare AI, from design, development, and validation to regulation, deployment, and monitoring.
| Publication Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science R Medicine > RA Public aspects of medicine |
| Departments: | School of Health & Medical Sciences School of Health & Medical Sciences > Midwifery & Radiography |
| SWORD Depositor: |
Available under License Creative Commons Attribution Non-commercial.
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