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Transparency and reproducibility in artificial intelligence

Nature volume 586, pages E14–E16 (2020)Cite this article

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Matters Arising to this article was published on 14 October 2020

The Original Article was published on 01 January 2020

arising from S. M. McKinney et al. Nature https://doi.org/10.1038/s41586-019-1799-6 (2020)

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Acknowledgements

We thank S. McKinney and colleagues for their prompt and open communication regarding the materials and methods of their study. This work was supported in part by the National Cancer Institute (R01 CA237170).

Author information

Authors and Affiliations

  1. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada

    Benjamin Haibe-Kains, Farnoosh Khodakarami & Michael M. Hoffman

  2. Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada

    Benjamin Haibe-Kains, Farnoosh Khodakarami, Bo Wang, Chris McIntosh & Michael M. Hoffman

  3. Department of Computer Science, University of Toronto, Toronto, Ontario, Canada

    Benjamin Haibe-Kains, George Alexandru Adam, Bo Wang, Anna Goldenberg & Michael M. Hoffman

  4. Ontario Institute for Cancer Research, Toronto, Ontario, Canada

    Benjamin Haibe-Kains

  5. Vector Institute for Artificial Intelligence, Toronto, Ontario, Canada

    Benjamin Haibe-Kains, George Alexandru Adam, Bo Wang, Chris McIntosh, Anna Goldenberg & Michael M. Hoffman

  6. Artificial Intelligence in Medicine (AIM) Program, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Ahmed Hosny & Hugo J. W. L. Aerts

  7. Radiation Oncology and Radiology, Dana-Farber Cancer Institute, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Ahmed Hosny & Hugo J. W. L. Aerts

  8. Department of Epidemiology and Biostatistics and Institute for Implementation Science in Population Health, CUNY Graduate School of Public Health and Health Policy, New York, NY, USA

    Levi Waldron

  9. Peter Munk Cardiac Centre, University Health Network, Toronto, Ontario, Canada

    Bo Wang & Chris McIntosh

  10. Department of Laboratory Medicine and Pathobiology, University of Toronto, Ontario, Canada

    Bo Wang

  11. SickKids Research Institute, Toronto, Ontario, Canada

    Anna Goldenberg

  12. Child and Brain Development Program, CIFAR, Toronto, Ontario, Canada

    Anna Goldenberg

  13. Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA

    Anshul Kundaje

  14. Department of Computer Science, Stanford University, Stanford, CA, USA

    Anshul Kundaje

  15. Dept. of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    Casey S. Greene

  16. Childhood Cancer Data Lab, Alex’s Lemonade Stand Foundation, Philadelphia, PA, USA

    Casey S. Greene

  17. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Tamara Broderick

  18. Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Jeffrey T. Leek

  19. Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada

    Keegan Korthauer

  20. BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada

    Keegan Korthauer

  21. European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany

    Wolfgang Huber

  22. European Molecular Biology Laboratory, European Bioinformatics Institute, EMBL-EBI, Hinxton, UK

    Alvis Brazma

  23. McGill University, Montreal, Quebec, Canada

    Joelle Pineau

  24. Montreal Institute for Learning Algorithms, Quebec, Canada

    Joelle Pineau

  25. Department of Statistics, Stanford University School of Humanities and Sciences, Stanford, CA, USA

    Robert Tibshirani, Trevor Hastie & John P. A. Ioannidis

  26. Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA, USA

    Robert Tibshirani, Trevor Hastie & John P. A. Ioannidis

  27. Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    John P. A. Ioannidis

  28. Meta-Research Innovation Center at Stanford (METRICS), Stanford, CA, USA

    John P. A. Ioannidis

  29. Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA

    John P. A. Ioannidis

  30. Department of Biostatistics, Harvard T.H Chan School of Public Health, Boston, MA, USA

    John Quackenbush

  31. Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    John Quackenbush

  32. Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, USA

    John Quackenbush

  33. Radiology and Nuclear Medicine, Maastricht University, Maastricht, The Netherlands

    Hugo J. W. L. Aerts

  34. Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA

    Hugo J. W. L. Aerts

  35. National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, USA

    Thakkar Shraddha & Weida Tong

  36. Immuneering Corporation, Cambridge, MA, USA

    Rebecca Kusko

  37. Engineering Science Department, Oxford e-Research Centre, University of Oxford, Oxford, UK

    Susanna-Assunta Sansone

  38. SAS Institute Inc, Cary, NC, USA

    Russ D. Wolfinger

  39. Weill Cornell Medicine, New York, NY, USA

    Christopher E. Mason

  40. Q2 Solutions, Morrisville, NC, USA

    Wendell Jones

  41. Hospital Virgen del Rocio, Sevilla, Spain

    Joaquin Dopazo

  42. Fondazione Bruno Kessler, Trento, Italy

    Cesare Furlanello

Authors
  1. Benjamin Haibe-Kains
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  2. George Alexandru Adam
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  3. Ahmed Hosny
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  4. Farnoosh Khodakarami
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  5. Levi Waldron
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  6. Bo Wang
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  7. Chris McIntosh
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  8. Anna Goldenberg
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  9. Anshul Kundaje
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  10. Casey S. Greene
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  11. Tamara Broderick
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  12. Michael M. Hoffman
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  13. Jeffrey T. Leek
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  14. Keegan Korthauer
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  15. Wolfgang Huber
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  16. Alvis Brazma
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  17. Joelle Pineau
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  18. Robert Tibshirani
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  19. Trevor Hastie
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  20. John P. A. Ioannidis
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  21. John Quackenbush
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  22. Hugo J. W. L. Aerts
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Consortia

Massive Analysis Quality Control (MAQC) Society Board of Directors

  • Thakkar Shraddha
  • , Rebecca Kusko
  • , Susanna-Assunta Sansone
  • , Weida Tong
  • , Russ D. Wolfinger
  • , Christopher E. Mason
  • , Wendell Jones
  • , Joaquin Dopazo
  •  & Cesare Furlanello

Contributions

B.H.-K. and G.A.A. wrote the first draft of the manuscript. B.H.-K. and H.J.W.L.A. designed and supervised the study. A.H., F.K., T.S., R.K., S.-A.S., W.T., R.D.W., C.E.M., W.J., J.D., C.F., L.W., B.W., C. McIntosh, A.G., A.K., C.S.G., T.B., M.M.H., J.T.L., K.K., W.H., A.B., J.P., R.T., T.H., J.P.A.I. and J.Q. contributed to the writing of the manuscript.

Corresponding author

Correspondence to Benjamin Haibe-Kains.

Ethics declarations

Competing interests

A.H. is a shareholder of and receives consulting fees from Altis Labs. M.M.H. received a GPU Grant from Nvidia. H.J.W.L.A. is a shareholder of and receives consulting fees from Onc.AI. B.H.K. is a scientific advisor for Altis Labs. C.M. holds an equity position in Bridge7Oncology and receives royalties from RaySearch Laboratories. A.K. is on the SAB of ImmuneAI Inc, a consultant for Biogen Inc., a scientific co-founder of RavelBio Inc. and a shareholder of Freenome Inc. G.A.A., F.K., L.W., B.W., C.S.G., J.T.L., W.H., A.B., J.P., R.T., T.H., J.P.A.I. and J.Q. declare no other competing interests related to the manuscript.

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Haibe-Kains, B., Adam, G.A., Hosny, A. et al. Transparency and reproducibility in artificial intelligence. Nature 586, E14–E16 (2020). https://doi.org/10.1038/s41586-020-2766-y

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