Attention-Based Multimodal Deep Learning for Uveal Melanoma Classification Using Ultra-Widefield Fundus Images and Ocular Ultrasound.

Uveal melanomas had a mean thickness of 6.0 mm and a basal diameter of 12.6 mm, whereas nevi measured 1.8 mm and 6.5 mm, respectively.

Among single-modality models, the model trained on transverse ultrasound images achieved the highest performance (accuracy: 92%; F1 score: 0.9227; AUC: 0.9538).

Averaging predictions from the single-modality models provided only modest gains because their outputs sometimes conflicted.