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The present study aimed to train deep convolutional neural networks (CNNs) to detect caries lesions on Near-Infrared Light Transillumination (NILT) imagery obtained either in vitro or in vivo and to assess the models' generalizability.

Generalizability of Deep Learning Models for Caries Detection in Near-Infrared Light Transillumination Images