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Comment
. 2023 May 12;4(5):283-284.
doi: 10.1016/j.medj.2023.04.002.

Deep learning for Mpox: Advances, challenges, and opportunities

Shannon Wongvibulsin  1 , Adewole S Adamson  2
Affiliations
Comment

Deep learning for Mpox: Advances, challenges, and opportunities

Shannon Wongvibulsin et al. Med. .

Abstract

Although deep-learning algorithms in dermatology have shown promise in diagnosing skin cancers, less is known about potential applications for the diagnosis of infectious diseases. In a recent publication in Nature Medicine, Thieme et al. develop a deep-learning algorithm to classify skin lesions from Mpox virus (MPXV) infections.1.

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Conflict of interest statement

Declaration of interests A.S.A. is a web and associate editor at JAMA Dermatology.

Comment on

  • A deep-learning algorithm to classify skin lesions from mpox virus infection.
    Thieme AH, Zheng Y, Machiraju G, Sadee C, Mittermaier M, Gertler M, Salinas JL, Srinivasan K, Gyawali P, Carrillo-Perez F, Capodici A, Uhlig M, Habenicht D, Löser A, Kohler M, Schuessler M, Kaul D, Gollrad J, Ma J, Lippert C, Billick K, Bogoch I, Hernandez-Boussard T, Geldsetzer P, Gevaert O. Thieme AH, et al. Nat Med. 2023 Mar;29(3):738-747. doi: 10.1038/s41591-023-02225-7. Epub 2023 Mar 2. Nat Med. 2023. PMID: 36864252 Free PMC article.

References

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    1. Esteva A., Kuprel B., Novoa R.A., Ko J., Swetter S.M., Blau H.M., Thrun S. Dermatologist-level classification of skin cancer with deep neural networks. Nat. 2017;542:115–118. - PMC - PubMed
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    1. Olsen L.A., Aisner D., McGinnis J.M. National Academies Press; 2007. The Learning Healthcare System. Learn Health Sys. - PubMed