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Addendum: International evaluation of an AI system for breast cancer screening

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• Addendum
• Published: 14 October 2020

Addendum: International evaluation of an AI system for breast cancer screening

• Scott Mayer McKinney, 
• Marcin Sieniek, 
• Varun Godbole, 
• Jonathan Godwin, 
• Natasha Antropova, 
• Hutan Ashrafian, 
• Trevor Back, 
• Mary Chesus, 
• Greg S. Corrado, 
• Ara Darzi, 
• Mozziyar Etemadi, 
• Florencia Garcia-Vicente, 
• Fiona J. Gilbert, 
• Mark Halling-Brown, 
• Demis Hassabis, 
• Sunny Jansen, 
• Alan Karthikesalingam, 
• Christopher J. Kelly, 
• Dominic King, 
• Joseph R. Ledsam, 
• David Melnick, 
• Hormuz Mostofi, 
• Lily Peng, 
• Joshua Jay Reicher, 
• …
• Shravya Shetty 

Nature volume 586, pageE19 (2020)Cite this article

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The Original Article was published on 01 January 2020

Addendum to: Nature https://doi.org/10.1038/s41586-019-1799-6 Published online 01 January 2020

To assist with the replication of our results, we have expanded the Supplementary Methods of our Article to provide more detail on how our deep learning system was trained. This includes additional optimization hyperparameters, as well as a more exhaustive description of the data augmentation strategy. Revised Supplementary Methods are presented in the Supplementary Information to this Addendum. Please also see the accompanying Matters Arising Comment (Haibe-Kains et al., https://doi.org/10.1038/s41686-020-2766-y)1 and Reply (McKinney et al., https://doi.org/10.1038/s41686-020-2767-x)2.

 In addition, the middle initial of author Greg Corrado should be ‘S’ rather than ‘C’. This error has been corrected online.

Supplementary Information is available in the online version of this Amendment.

References

1. Haibe-Kains, B. et al. Transparency and reproducibility in artificial intelligence. Nature https://doi.org/10.1038/s41586-020-2766-y (2020).

2. McKinney, S. M. et al. Reply to: Transparency and reproducibility in artificial intelligence. Nature https://doi.org/10.1038/s41586-020-2767-x (2020).

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Author information

Author notes

1. These authors contributed equally: Scott Mayer McKinney, Marcin T. Sieniek, Varun Godbole, Jonathan Godwin

2. These authors jointly supervised this work: Jeffrey De Fauw, Shravya Shetty

Authors and Affiliations

1. Google Health, Palo Alto, CA, USA

   Scott Mayer McKinney, Marcin Sieniek, Varun Godbole, Greg S. Corrado, Hormuz Mostofi, Lily Peng, Daniel Tse & Shravya Shetty

2. DeepMind, London, UK

   Jonathan Godwin, Natasha Antropova, Trevor Back, Mary Chesus, Demis Hassabis, Joseph R. Ledsam, Bernardino Romera-Paredes, Mustafa Suleyman & Jeffrey De Fauw

3. Department of Surgery and Cancer, Imperial College London, London, UK

   Hutan Ashrafian & Ara Darzi

4. Institute of Global Health Innovation, Imperial College London, London, UK

   Hutan Ashrafian & Ara Darzi

5. Cancer Research UK Imperial Centre, Imperial College London, London, UK

   Ara Darzi

6. Northwestern Medicine, Chicago, IL, USA

   Mozziyar Etemadi, Florencia Garcia-Vicente & David Melnick

7. Department of Radiology, Cambridge Biomedical Research Centre, University of Cambridge, Cambridge, UK

   Fiona J. Gilbert

8. Royal Surrey County Hospital, Guildford, UK

   Mark Halling-Brown & Kenneth C. Young

9. Verily Life Sciences, South San Francisco, CA, USA

   Sunny Jansen

10. Google Health, London, UK

    Alan Karthikesalingam, Christopher J. Kelly & Dominic King

11. Stanford Health Care and Palo Alto Veterans Affairs, Palo Alto, CA, USA

    Joshua Jay Reicher

12. The Royal Marsden Hospital, London, UK

    Richard Sidebottom

13. Thirlestaine Breast Centre, Cheltenham, UK

    Richard Sidebottom

Corresponding authors

Correspondence to Scott Mayer McKinney, Daniel Tse or Shravya Shetty.

Supplementary information

This file contains revised Supplementary Methods

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McKinney, S.M., Sieniek, M., Godbole, V. et al. Addendum: International evaluation of an AI system for breast cancer screening. Nature 586, E19 (2020). https://doi.org/10.1038/s41586-020-2679-9

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• Published14 October 2020

• Issue Date15 October 2020

• DOIhttps://doi.org/10.1038/s41586-020-2679-9

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Subjects

• Breast cancer
• Preclinical research

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