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

AI / informaticsNPJ digital medicine· Mar 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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OculoplasticsAI / informaticsDiagnosisQ1IF 18.0

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 · Mar 2025 · Q1 in General Medicine

Background

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

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Results

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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.

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

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

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