RESUMEN

In recent years,deep learning,a pivotal subset of artificial intelligence machine learning,has achieved noteworthy advancements in the medical domain.It facilitates precise detection,diagnosis and prognostic assessment of various diseases through the analysis of medical images.Within ophthalmology,deep learning techniques have found wide-spread application in the diagnosis and prediction of thyroid-related eye diseases,orbital blowout fracture,melanoma,bas-al cell carcinoma,orbital abscess,lymphoma,retinoblastoma and other diseases.Leveraging images from computed tomo-graphy,magnetic resonance imaging and even pathological sections,this technology demonstrates a capacity to diagnose,differentiate and stage orbital diseases and ocular tumors with a high level of accuracy comparable to that of expert clini-cians.The promising prospects of this technology are expected to enhance the diagnosis and treatment of related diseases,concurrently reducing the time and cost associated with clinical practices.This review consolidates the latest research pro-gress on the application of artificial intelligence deep learning in orbital diseases and ocular tumors,aiming to furnish clini-cians with up-to-date information and developmental trends in this field,thereby furthering the clinical application and widespread adoption of this technology.