Smartphone-Based Proactive Self-Screening for Ocular Surface Malignancies

Can a smartphone-based artificial intelligence system integrated with mass media outreach enable large-scale screening for rare ocular surface malignancies in the general population?In this nonrandomized clinical trial, the smartphone-optimized CaptureTumor application achieved diagnostic accuracy comparable with that of specialist-graded slitlamp evaluation. This application demonstrated accuracy for malignancy detection and identified cases with 5-fold greater efficiency than conventional hospital-based referral pathways.These findings suggest that combining smartphone photography, artificial intelligence, and media-facilitated public engagement can establish a scalable and accessible model for population screening of rare sight and life-threatening ocular tumors, advancing early detection and health equity for underrecognized conditions.

Corresponding Authors: Haotian Lin, MD, PhD (linht5@mail.sysu.edu.cn), Huijing Ye (yehuijing@gzzoc.com), and Ruixin Wang (wangruixin@gzzoc.com), Zhongshan Ophthalmic Center, Sun Yat-sen University, 7 Jinsui Rd, Guangzhou 510623, China.

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