Item request has been placed! ×
Item request cannot be made. ×
loading  Processing Request

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Item request has been placed! ×
Item request cannot be made. ×
loading   Processing Request
  • Additional Information
    • Publication Information:
      BMJ Publishing Group
    • Publication Date:
      2025
    • 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. ; sponsorship: This work has been supported by the European Union's Horizon 2020 under grant agreement No 952159 (ProCAncer-I) , No 952172 (CHAIMELEON) , No 826494 (PRIMAGE) , No 952179 (INCISIVE) , No 101034347 (OPTIMA) , No 101016775 (INTERVENE) , No 101100633 (EUCAIM) , No 101136670 (GLIOMATCH) , No 101057062 (AIDAVA) , No 101095435 (REALM) , and No 116074 (BigData@Heart) . This work received support from the European Union's Horizon Europe under grant agreement No 101057699 (RadioVal) , No 101057849 (DataTools4Heart) , and No 101080430 (AI4HF) . This work received support from the European Research Council under grant agreement No 757173 (MIRA) , No 884622 (Deep4MI) , No 101002198 (NEURALSPICING) , No 866504 (CANCER-RADIOMICS) , and No 101044779 (AIMIX) . This work was partially supported by the Royal Academy of Engineering, Hospital Clinic Barcelona, Malaria No More, Carnegie Cooperation New York, Human frontier science programme, Natural Sciences and Engineering Research Council of Canada ...
    • File Description:
      application/pdf
    • Relation:
      https://lirias.kuleuven.be/handle/20.500.12942/766092; https://lirias.kuleuven.be/retrieve/812153; https://pubmed.ncbi.nlm.nih.gov/39909534
    • Accession Number:
      10.1136/bmj-2024-081554
    • Online Access:
      https://lirias.kuleuven.be/handle/20.500.12942/766092
      https://hdl.handle.net/20.500.12942/766092
      https://lirias.kuleuven.be/retrieve/812153
      https://doi.org/10.1136/bmj-2024-081554
      https://pubmed.ncbi.nlm.nih.gov/39909534
    • Rights:
      info:eu-repo/semantics/openAccess ; public ; https://creativecommons.org/licenses/by/4.0/
    • Accession Number:
      edsbas.8A869A3D