Development and deployment of a smartphone application for diagnosing trachoma: Leveraging code-free deep learning and edge artificial intelligence

Ophthalmology's new horizon: Moving from reactive care to proactive artificial intelligence solutions

“…[10] Another Guest Editorial highlights its efficacy in trachoma detection. [11] Notably, the trachoma detection algorithm created with autoML outperformed an algorithm created by AI experts for the same dataset. A significant feature of both these AutoML applications is their ability to operate offline, emphasizing their adaptability and versatility in various settings.…”