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New research · Ophthalmology
NPJ digital medicine · 5d
AI / informaticsNPJ digital medicine · 2025

Deep learning-based mobile application for efficient eyelid tumor recognition in clinical images.

Shiqi Hui, Jing Xie, Li Dong … Dongmei Li
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OphthalmologyAI / informatics

Smartphone app classified eyelid photos as benign, malignant, or normal with high accuracy.

Deep learning-based mobile application for efficient eyelid tumor recognition in clinical images.

Shiqi Hui … Dongmei Li
NPJ digital medicine · 2025
Background

Early detection, regular monitoring of eyelid tumors and post-surgery recurrence monitoring are crucial for patients.

0.921
Results
0.921
app correctly identified the eyelid condition in about 92% of cases
n = 1195 preprocessed clinical ocular
More results

However, frequent hospital visits are burdensome for patients with poor medical conditions.

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Conclusion

Intelligent Eyelid Tumor Screening application exhibited a straightforward detection process, user-friendly interface and treatment recommendation scheme, provides preliminary evidence for recognizing eyelid tumors and could be used by healthcare professionals, patients and caregivers for detection and monitoring purposes.

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