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Lessons learned from translating AI from development to deployment in healthcare

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The application of an artificial intelligence (AI)-based screening tool for retinal disease in India and Thailand highlighted the myths and reality of introducing medical AI, which may form a framework for subsequent tools

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Fig. 1: Myths and reality of developing medical AI.

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Acknowledgements

We thank the Google and Verily teams involved in developing, delivering, and improving ARDA. We also thank to C. Chen and M. Howell for manuscript feedback and A. Iurchenko for the illustration concept. Our work was inspired by our partners continuously expanding access to high quality care such as R. Kim and his team at the Aravind Eye Hospital, P. Ruamviboonsuk and his team at the Rajavithi Hospital in Thailand, and J. Cuadros and his team at EyePACS.

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  1. Lily Peng

    Present address: Verily, South San Francisco, CA, USA

Authors and Affiliations

  1. Google Health, Palo Alto, CA, USA

    Kasumi Widner, Sunny Virmani, Jonathan Krause, Jay Nayar, Richa Tiwari, Elin Rønby Pedersen, Divleen Jeji, Naama Hammel, Yossi Matias, Greg S. Corrado, Yun Liu, Lily Peng & Dale R. Webster

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  1. Kasumi Widner
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Correspondence to Yun Liu.

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All authors are employees of Google LLC and own Alphabet stock.

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Widner, K., Virmani, S., Krause, J. et al. Lessons learned from translating AI from development to deployment in healthcare. Nat Med 29, 1304–1306 (2023). https://doi.org/10.1038/s41591-023-02293-9

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