Artificial intelligence to detect malignant eyelid tumors from photographic images

作者：Zhongwen Li, Zhongwen Li, Wei Qiang, Hongyun Chen, Mengjie Pei, Xiaomei Yu, Layi Wang, Zhen Li, Zhen Li, Weiwei Xie, Guohai Wu, Jiewei Jiang, Guohai Wu · 发表于：npj Digital Medicine · 年份：2022 · DOI：10.1038/s41746-022-00571-3 · 被引用次数：64 · 研究领域：Nonmelanoma Skin Cancer Studies、Cutaneous Melanoma Detection and Management、Ocular Oncology and Treatments

Malignant eyelid tumors can invade adjacent structures and pose a threat to vision and even life. Early identification of malignant eyelid tumors is crucial to avoiding substantial morbidity and mortality. However, differentiating malignant eyelid tumors from benign ones can be challenging for primary care physicians and even some ophthalmologists. Here, based on 1,417 photographic images from 851 patients across three hospitals, we developed an artificial intelligence system using a faster region-based convolutional neural network and deep learning classification networks to automatically locate eyelid tumors and then distinguish between malignant and benign eyelid tumors. The system performed well in both internal and external test sets (AUCs ranged from 0.899 to 0.955). The performance of the system is comparable to that of a senior ophthalmologist, indicating that this system has the potential to be used at the screening stage for promoting the early detection and treatment of malignant eyelid tumors.