. 2025 Feb 5:388:e081554.

doi: 10.1136/bmj-2024-081554.

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

Karim Lekadir^{1

2}, Alejandro F Frangi^{3

4}, Antonio R Porras⁵, Ben Glocker⁶, Celia Cintas⁷, Curtis P Langlotz⁸, Eva Weicken⁹, Folkert W Asselbergs^{10

11}, Fred Prior¹², Gary S Collins¹³, Georgios Kaissis¹⁴, Gianna Tsakou¹⁵, Irène Buvat¹⁶, Jayashree Kalpathy-Cramer¹⁷, John Mongan¹⁸, Julia A Schnabel¹⁹, Kaisar Kushibar¹, Katrine Riklund²⁰, Kostas Marias²¹, Lameck M Amugongo²², Lauren A Fromont²³, Lena Maier-Hein²⁴, Leonor Cerdá-Alberich²⁵, Luis Martí-Bonmatí²⁶, M Jorge Cardoso²⁷, Maciej Bobowicz²⁸, Mahsa Shabani²⁹, Manolis Tsiknakis²¹, Maria A Zuluaga³⁰, Marie-Christine Fritzsche³¹, Marina Camacho¹, Marius George Linguraru³², Markus Wenzel⁹, Marleen De Bruijne³³, Martin G Tolsgaard³⁴, Melanie Goisauf³⁵, Mónica Cano Abadía³⁵, Nikolaos Papanikolaou³⁶, Noussair Lazrak¹, Oriol Pujol¹, Richard Osuala¹, Sandy Napel³⁷, Sara Colantonio³⁸, Smriti Joshi¹, Stefan Klein³³, Susanna Aussó³⁹, Wendy A Rogers⁴⁰, Zohaib Salahuddin⁴¹, Martijn P A Starmans³³; FUTURE-AI Consortium

Collaborators, Affiliations

Collaborators

FUTURE-AI Consortium:
Aasa Feragen, Abdul Joseph Fofanah, Alena Buyx, Anais Emelie, Andrea Lara, An-Wen Chan, Arcadi Navarro, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Fabio A González, Gabriel P Krestin, Geletaw S Tegenaw, Gianluca Misuraca, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Horst Joachim Mayer, Hugo Jwl Aerts, Ian Walsh, Ioanna Chouvarda, Isabell Tributsch, Islem Rekik, James Duncan, Jihad Zahir, Jinah Park, Judy W Gichoya, Kensaku Mori, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Maria Bielikova, Marzyeh Ghassemi, Md Ashrafuzzaman, Mohammad Yaqub, Mukhtar M E Mahmoud, Mustafa Elattar, Nicola Rieke, Oliver Díaz, Olivier Salvado, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Rose Nakasi, S Kevin Zhou, Shadi Albarqouni, Stacy Carter, Steffen E Petersen, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe E M Mutsvangwa, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino

Affiliations

¹ Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.
² Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
³ Center for Computational Imaging & Simulation Technologies in Biomedicine, Schools of Computing and Medicine, University of Leeds, Leeds, UK.
⁴ Medical Imaging Research Centre (MIRC), Cardiovascular Science and Electronic Engineering Departments, KU Leuven, Leuven, Belgium.
⁵ Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
⁶ Department of Computing, Imperial College London, London, UK.
⁷ IBM Research Africa, Nairobi, Kenya.
⁸ Departments of Radiology, Medicine, and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
⁹ Fraunhofer Heinrich Hertz Institute, Berlin, Germany.
¹⁰ Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Amsterdam, Netherlands.
¹¹ Health Data Research UK and Institute of Health Informatics, University College London, London, UK.
¹² Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
¹³ Centre for Statistics in Medicine, University of Oxford, Oxford, UK.
¹⁴ Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany.
¹⁵ Gruppo Maggioli, Research and Development Lab, Athens, Greece.
¹⁶ Institut Curie, Inserm, Orsay, France.
¹⁷ Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
¹⁹ Institute of Machine Learning in Biomedical Imaging, Helmholtz Center Munich, Munich, Germany.
²⁰ Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden.
²¹ Foundation for Research and Technology-Hellas (FORTH), Crete, Greece.
²² Department of Software Engineering, Namibia University of Science & Technology, Windhoek, Namibia.
²³ Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
²⁴ Division of Intelligent Medical Systems, German Cancer Research Centre, Heidelberg, Germany.
²⁵ Biomedical Imaging Research Group, La Fe Health Research Institute, Valencia, Spain.
²⁶ Medical Imaging Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
²⁷ School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
²⁸ 2nd Division of Radiology, Medical University of Gdansk, Gdansk, Poland.
²⁹ Faculty of Law and Criminology, Ghent University, Ghent, Belgium.
³⁰ Data Science Department, EURECOM, Sophia Antipolis, France.
³¹ Institute of History and Ethics in Medicine, Technical University of Munich, Munich, Germany.
³² Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington DC, USA.
³³ Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Centre, Rotterdam, Netherlands.
³⁴ Copenhagen Academy for Medical Education and Simulation Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
³⁵ BBMRI-ERIC, ELSI Services & Research, Graz, Austria.
³⁶ Computational Clinical Imaging Group, Champalimaud Foundation, Lisbon, Portugal.
³⁷ Integrative Biomedical Imaging Informatics at Stanford (IBIIS), Department of Radiology, Stanford University, Stanford, CA, USA.
³⁸ Institute of Information Science and Technologies of the National Research Council of Italy, Pisa, Italy.
³⁹ Artificial Intelligence in Healthcare Program, TIC Salut Social Foundation, Barcelona, Spain.
⁴⁰ Department of Philosophy, and School of Medicine, Macquarie University, Sydney, Australia.
⁴¹ The D-lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.

PMID: 39909534
PMCID: PMC11795397
DOI: 10.1136/bmj-2024-081554

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

Karim Lekadir et al. BMJ. 2025.

. 2025 Feb 5:388:e081554.

doi: 10.1136/bmj-2024-081554.

Authors

Collaborators

FUTURE-AI Consortium:
Aasa Feragen, Abdul Joseph Fofanah, Alena Buyx, Anais Emelie, Andrea Lara, An-Wen Chan, Arcadi Navarro, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Fabio A González, Gabriel P Krestin, Geletaw S Tegenaw, Gianluca Misuraca, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Horst Joachim Mayer, Hugo Jwl Aerts, Ian Walsh, Ioanna Chouvarda, Isabell Tributsch, Islem Rekik, James Duncan, Jihad Zahir, Jinah Park, Judy W Gichoya, Kensaku Mori, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Maria Bielikova, Marzyeh Ghassemi, Md Ashrafuzzaman, Mohammad Yaqub, Mukhtar M E Mahmoud, Mustafa Elattar, Nicola Rieke, Oliver Díaz, Olivier Salvado, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Rose Nakasi, S Kevin Zhou, Shadi Albarqouni, Stacy Carter, Steffen E Petersen, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe E M Mutsvangwa, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino

Affiliations

¹ Artificial Intelligence in Medicine Lab (BCN-AIM), Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Barcelona, Spain.
² Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.
³ Center for Computational Imaging & Simulation Technologies in Biomedicine, Schools of Computing and Medicine, University of Leeds, Leeds, UK.
⁴ Medical Imaging Research Centre (MIRC), Cardiovascular Science and Electronic Engineering Departments, KU Leuven, Leuven, Belgium.
⁵ Department of Biostatistics and Informatics, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
⁶ Department of Computing, Imperial College London, London, UK.
⁷ IBM Research Africa, Nairobi, Kenya.
⁸ Departments of Radiology, Medicine, and Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA.
⁹ Fraunhofer Heinrich Hertz Institute, Berlin, Germany.
¹⁰ Amsterdam University Medical Centers, Department of Cardiology, University of Amsterdam, Amsterdam, Netherlands.
¹¹ Health Data Research UK and Institute of Health Informatics, University College London, London, UK.
¹² Department of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
¹³ Centre for Statistics in Medicine, University of Oxford, Oxford, UK.
¹⁴ Institute for AI and Informatics in Medicine, Klinikum rechts der Isar, Technical University Munich, Munich, Germany.
¹⁵ Gruppo Maggioli, Research and Development Lab, Athens, Greece.
¹⁶ Institut Curie, Inserm, Orsay, France.
¹⁷ Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
¹⁸ Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
¹⁹ Institute of Machine Learning in Biomedical Imaging, Helmholtz Center Munich, Munich, Germany.
²⁰ Department of Radiation Sciences, Diagnostic Radiology, Umeå University, Umeå, Sweden.
²¹ Foundation for Research and Technology-Hellas (FORTH), Crete, Greece.
²² Department of Software Engineering, Namibia University of Science & Technology, Windhoek, Namibia.
²³ Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
²⁴ Division of Intelligent Medical Systems, German Cancer Research Centre, Heidelberg, Germany.
²⁵ Biomedical Imaging Research Group, La Fe Health Research Institute, Valencia, Spain.
²⁶ Medical Imaging Department, Hospital Universitario y Politécnico La Fe, Valencia, Spain.
²⁷ School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK.
²⁸ 2nd Division of Radiology, Medical University of Gdansk, Gdansk, Poland.
²⁹ Faculty of Law and Criminology, Ghent University, Ghent, Belgium.
³⁰ Data Science Department, EURECOM, Sophia Antipolis, France.
³¹ Institute of History and Ethics in Medicine, Technical University of Munich, Munich, Germany.
³² Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital, Washington DC, USA.
³³ Department of Radiology & Nuclear Medicine, Erasmus MC University Medical Centre, Rotterdam, Netherlands.
³⁴ Copenhagen Academy for Medical Education and Simulation Rigshospitalet, University of Copenhagen, Copenhagen, Denmark.
³⁵ BBMRI-ERIC, ELSI Services & Research, Graz, Austria.
³⁶ Computational Clinical Imaging Group, Champalimaud Foundation, Lisbon, Portugal.
³⁷ Integrative Biomedical Imaging Informatics at Stanford (IBIIS), Department of Radiology, Stanford University, Stanford, CA, USA.
³⁸ Institute of Information Science and Technologies of the National Research Council of Italy, Pisa, Italy.
³⁹ Artificial Intelligence in Healthcare Program, TIC Salut Social Foundation, Barcelona, Spain.
⁴⁰ Department of Philosophy, and School of Medicine, Macquarie University, Sydney, Australia.
⁴¹ The D-lab, Department of Precision Medicine, GROW-School for Oncology and Reproduction, Maastricht University, Maastricht, Netherlands.

PMID: 39909534
PMCID: PMC11795397
DOI: 10.1136/bmj-2024-081554

Erratum in

FUTURE-AI: international consensus guideline for trustworthy and deployable artificial intelligence in healthcare.
[No authors listed] [No authors listed] BMJ. 2025 Feb 17;388:r340. doi: 10.1136/bmj.r340. BMJ. 2025. PMID: 39961614 Free PMC article. No abstract available.

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.

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Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from European Union’s Horizon 2020 for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. GD owns equity interest in Artrya Ltd and provides consultancy services. JK-C receives research funding from GE, Genetech and is a consultant at Siloam Vision. GPK advises some AI startups such as Gleamer.AI, FLUIDDA BV, NanoX Vision and was the founder of Quantib BV. SEP is a consultant for Circle Cardiovascular Imaging, Calgary, Alberta, Canada. BG is employed by Kheiron Medical Technologies and HeartFlow. PL has/had grants/sponsored research agreements from Radiomics SA, Convert Pharmaceuticals SA and LivingMed Biotech srl. He received a presenter fee and/or reimbursement of travel costs/consultancy fee (in cash or in kind) from Astra Zeneca, BHV srl, and Roche. PL has/had minority shares in the companies Radiomics SA, Convert pharmaceuticals SA, Comunicare SA, LivingMed Biotech srl, and Bactam srl. PL is co-inventor of two issued patents with royalties on radiomics (PCT/NL2014/050248 and PCT/NL2014/050728), licensed to Radiomics SA; one issued patent on mtDNA (PCT/EP2014/059089), licensed to ptTheragnostic/DNAmito; one granted patent on LSRT (PCT/ P126537PC00, US patent No 12 102 842), licensed to Varian; one issued patent on Radiomic signature of hypoxia (US patent No 11 972 867), licensed to a commercial entity; one issued patent on Prodrugs (WO2019EP64112) without royalties; one non-issued, non-licensed patents on Deep Learning-Radiomics (N2024889) and three non-patented inventions (softwares) licensed to ptTheragnostic/DNAmito, Radiomics SA and Health Innovation Ventures. ARP serves as advisor for mGeneRX in exchange for equity. JM receives royalties from GE, research grants from Siemens and is unpaid consultant for Nuance. HCW owns minority shares in the company Radiomics SA. JWG serves on several radiology society AI committees. LR advises an AI startup Neurlamind. CPL is a shareholder and advisor to Bunker Hill Health, GalileoCDS, Sirona Medical, Adra, and Kheiron Medical. He serves as a board member of Bunker Hill Health and a shareholder of whiterabbit.ai. He has served as a paid consultant to Sixth Street and Gilmartin Capital. His institution has received grants or gifts from Bunker Hill Health, Carestream, CARPL, Clairity, GE Healthcare, Google Cloud, IBM, Kheiron, Lambda, Lunit, Microsoft, Philips, Siemens Healthineers, Stability.ai, Subtle Medical, VinBrain, Visiana, Whiterabbit.ai, the Lowenstein Foundation, and the Gordon and Betty Moore Foundation. GSC is a statistics editor for the BMJ and a National Institute for Health and Care Research (NIHR) Senior Investigator. The views expressed in this article are those of the author(s) and not necessarily those of the NIHR, or the Department of Health and Social Care. All other authors declare no competing interests.

Figures

**Fig 1**
Geographical distribution of the multidisciplinary experts

**Fig 2**
Organisation of the FUTURE-AI framework for trustworthy artificial intelligence (AI) according to six guiding principles—fairness, universality, traceability, usability, robustness, and explainability

**Fig 3**
Embedding the FUTURE-AI best practices into an agile process throughout the artificial intelligence (AI) lifecycle. E=explainability; F=fairness; G=general; R=robustness; T=traceability; Un=universality; Us=usability

See this image and copyright information in PMC

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

Collaborators

Affiliations

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

Authors

Collaborators

Affiliations

Erratum in

Abstract

Conflict of interest statement

Figures

References

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