Integrating artificial intelligence in strabismus management: current research landscape and future directions - Dawen Wu; Dawen Wu; Xi Huang; Xi Huang; Liang Chen; Liang Chen; Peixian Hou; Peixian Hou; Longqian Liu; Longqian Liu; Guoyuan Yang; Guoyuan Yang (Experimental Biology and Medicine)
Advancements in artificial intelligence (AI) are transforming strabismus management through improved screening, diagnosis, and surgical planning. Deep learning has notably enhanced diagnostic accuracy and optimized surgical outcomes. Despite these advancements, challenges such as the underrepresentation of diverse strabismus types and reliance on single-source data remain prevalent. Emphasizing the need for inclusive AI systems, future research should focus on expanding AI capabilities with large model technologies, integrating multimodal data to bridge existing gaps, and developing integrated management platforms to better accommodate diverse patient demographics and clinical scenarios.