Closing the AI generalization gap by adjusting for dermatology condition
distribution differences across clinical settings
Closing the AI generalization gap by adjusting for dermatology condition
distribution differences across clinical settings
Recently, there has been great progress in the ability of artificial intelligence (AI) algorithms to classify dermatological conditions from clinical photographs. However, little is known about the robustness of these algorithms in real-world settings where several factors can lead to a loss of generalizability. Understanding and overcoming these limitations will …