FUTURE-AI: International consensus guideline for trustworthy and
  deployable artificial intelligence in healthcare
Karim Lekadir Aasa Feragen Abdul Joseph Fofanah Alejandro F Frangi Alena Buyx Anais Emelie Andrea Lara Antonio R Porras An-Wen Chan Arcadi Navarro Ben Glocker Benard O Botwe Bishesh Khanal Brigit Beger Carol C Wu Celia Cintas Curtis P Langlotz Daniel Rueckert Deogratias Mzurikwao Dimitrios I Fotiadis Doszhan Zhussupov Enzo Ferrante Erik Meijering Eva Weicken Fabio A González Folkert W Asselbergs Fred Prior Gabriel P Krestin Gary Collins Geletaw S Tegenaw Georgios Kaissis Gianluca Misuraca Gianna Tsakou Girish Dwivedi Haridimos Kondylakis Harsha Jayakody Henry C Woodruf Hugo JWL Aerts Ian Walsh Ioanna Chouvarda Irène Buvat Islem Rekik James Duncan Jayashree Kalpathy-Cramer Jihad Zahir Jinah Park John Mongan Judy W Gichoya Julia A Schnabel Kaisar Kushibar Katrine Riklund Kensaku Mori Kostas Marias Lameck M Amugongo Lauren A Fromont Lena Maier-Hein Leonor Cerdá Alberich Leticia Rittner Lighton Phiri Linda Marrakchi-Kacem Lluís Donoso-Bach Luis Martí-Bonmatí M Jorge Cardoso Maciej Bobowicz Mahsa Shabani Manolis Tsiknakis Maria A Zuluaga Maria Bielikova Marie-Christine Fritzsche Marius George Linguraru Markus Wenzel Marleen De Bruijne Martin G Tolsgaard Marzyeh Ghassemi Md Ashrafuzzaman Melanie Goisauf Mohammad Yaqub Mohammed Ammar Mónica Cano Abadía Mukhtar M E Mahmoud Mustafa Elattar Nicola Rieke Nikolaos Papanikolaou Noussair Lazrak Oliver Díaz Olivier Salvado Oriol Pujol Ousmane Sall Pamela Guevara Peter Gordebeke Philippe Lambin Pieta Brown Purang Abolmaesumi Qi Dou Qinghua Lu Richard Osuala Rose Nakasi S Kevin Zhou Sandy Napel Sara Colantonio Shadi Albarqouni Smriti Joshi Stacy Carter Stefan Klein Steffen E Petersen Susanna Aussó Suyash Awate Tammy Riklin Raviv Tessa Cook Tinashe E M Mutsvangwa Wendy A Rogers Wiro J Niessen Xènia Puig-Bosch Yi Zeng Yunusa G Mohammed Yves Saint James Aquino Zohaib Salahuddin Martijn P A Starmans
Despite major advances in artificial intelligence (AI) for medicine and
healthcare, the deployment and adoption of AI technologies remain limited in
real-world clinical practice. In recent years, concerns have been raised about
the technical, clinical, ethical and legal risks associated with medical AI. To
increase real world adoption, it is essential that medical AI tools are trusted
and accepted by patients, clinicians, health organisations and authorities.
This work describes the FUTURE-AI guideline as the first international
consensus framework for guiding the development and deployment of trustworthy
AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and
currently comprises 118 inter-disciplinary experts from 51 countries
representing all continents, including AI scientists, clinicians, ethicists,
and social scientists. Over a two-year period, the consortium defined guiding
principles and best practices for trustworthy AI through an iterative process
comprising an in-depth literature review, a modified Delphi survey, and online
consensus meetings. The FUTURE-AI framework was established based on 6 guiding
principles for trustworthy AI in healthcare, i.e. Fairness, Universality,
Traceability, Usability, Robustness and Explainability. Through consensus, a
set of 28 best practices were defined, addressing technical, clinical, legal
and socio-ethical dimensions. The recommendations cover the entire lifecycle of
medical AI, from design, development and validation to regulation, deployment,
and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which
provides a structured approach for constructing medical AI tools that will be
trusted, deployed and adopted in real-world practice. Researchers are
encouraged to take the recommendations into account in proof-of-concept stages
to facilitate future translation towards clinical practice of medical AI.