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9th World Congress of Teledermatology, Imaging and AI for Skin Diseases - Abstracts (2021) (40)
Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35391, first published .
Assessing Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists

Assessing Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists

Assessing Generalizability of Deep Learning Models Trained on Standardized and Nonstandardized Images and Their Performance Against Teledermatologists

Authors of this article:

Ibukun Oloruntoba1 Author Orcid Image ;   Toan D Nguyen2 Author Orcid Image ;   Zongyuan Ge3 Author Orcid Image ;   Tine Vestergaard4 Author Orcid Image ;   Victoria Mar5 Author Orcid Image
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Ibukun Oloruntoba   1 ;   Toan D Nguyen   2 , PhD ;   Zongyuan Ge   3 , PhD ;   Tine Vestergaard   4 , MD, PhD ;   Victoria Mar   5 , MBBS, FACD, PhD

1 School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

2 Monash University, Melbourne, Australia

3 Monash eResearch Centre, Monash University, Melbourne, Australia

4 Department of Dermatology and Allergy Centre, Odense University Hospital, Odense, Denmark

5 Victorian Melanoma Service, Alfred Health and School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia

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