Notice: Users may be experiencing issues with displaying some pages on stanfordhealthcare.org. We are working closely with our technical teams to resolve the issue as quickly as possible. Thank you for your patience.
We are available to assist you 24/7.
New to MyHealth?
Manage Your Care From Anywhere.
Access your health information from any device with MyHealth. You can message your clinic, view lab results, schedule an appointment, and pay your bill.
Automated Classification of Skin Lesions: From Pixels to Practice. The Journal of investigative dermatology Narla, A., Kuprel, B., Sarin, K., Novoa, R., Ko, J. 2018; 138 (10): 2108–10
The letters "Interpretation of the Outputs of Deep Learning Model trained with Skin Cancer Dataset" and "Automated Dermatological Diagnosis: Hype or Reality?" highlight the opportunities, hurdles, and possible pitfalls with the development of tools that allow for automated skin lesion classification. The potential clinical impact of these advances relies on their scalability, accuracy, and generalizability across a range of diagnostic scenarios.
View details for PubMedID 30244720