Artificial Intelligence in Oculoplastics: A Review.

Area of Science:

• Ophthalmology
• Medical Artificial Intelligence
• Oculoplastics

Background:

• Artificial intelligence (AI) is increasingly used for disease analysis in ophthalmology.
• Previous AI applications have focused on anterior and posterior segment diseases.
• The role of AI in oculoplastic conditions requires further investigation.

Purpose of the Study:

• To review the existing literature on the application of AI in oculoplastic diseases.
• To identify current AI uses and potential future directions in oculoplastics.

Main Methods:

• A comprehensive literature search was performed on Pubmed and Embase.
• Keywords included AI combined with various oculoplastic terms (e.g., ptosis, eyelid cancer, thyroid eye disease).
• AI large language models were excluded from the review.

Main Results:

• The review encompassed studies on eyelid and brow ptosis (19), periocular and intraocular cancer (16), orbital trauma and tumors (9), inflammatory/infectious orbital conditions (17), and thyroid eye disease (30).
• AI applications focused on diagnosis, severity assessment, and outcome prediction for these conditions.
• Specific AI uses include diagnosing ptosis, detecting eyelid cancer from images, and monitoring thyroid eye disease.

Conclusions:

• AI demonstrates expanding potential in oculoplastics, particularly for diagnosing conditions like ptosis and eyelid cancer.
• AI is also being explored for orbital tumors, radiographic image evaluation, and thyroid eye disease management.
• Significant challenges include data privacy, ethical concerns, data standardization, and the need for ongoing clinical validation of AI tools.