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Updated: Jul 26, 2025
Author Spotlight: Anterior HR-OCT as a Non-Invasive Tool for Characterizing Ocular Surface Squamous Neoplasia
Published on: August 9, 2024
Artificial intelligence for ocular oncology
Neslihan Dilruba Koseoglu1, Zélia Maria Corrêa2,3, T Y Alvin Liu1
1Wilmer Eye Institute, Johns Hopkins University, Baltimore, Maryland.
Purpose Of Review:
The aim of this article is to provide an update on the latest applications of deep learning (DL) and classical machine learning (ML) techniques to the detection and prognostication of intraocular and ocular surface malignancies.
Recent Findings:
Most recent studies focused on using DL and classical ML techniques for prognostication purposes in patients with uveal melanoma (UM).
Summary:
DL has emerged as the leading ML technique for prognostication in ocular oncological conditions, particularly in UM. However, the application of DL may be limited by the relatively rarity of these conditions.
