Qurban Qirat, Cassidy Lorraine
Department of Ophthalmology and Oculoplastic, Royal Victoria Eye and Ear Hospital, Dublin, Ireland.
Trinity College Dublin, Dublin, Ireland.
SAGE Open Med. 2024 Aug 27;12:20503121241274197. doi: 10.1177/20503121241274197. eCollection 2024.
In our article, we explore the transformative potential of Artificial Intelligence and Machine Learning in oculo-oncology, focusing on the diagnosis and management of ocular adnexal tumors. Delving into the intricacies of adnexal conditions such as conjunctival melanoma and squamous conjunctival carcinoma, the study emphasizes recent breakthroughs, such as Artificial Intelligence-driven early detection methods. While acknowledging challenges like the scarcity of specialized datasets and issues in standardizing image capture, the research underscores encouraging patient acceptance, as demonstrated in melanoma diagnosis studies. The abstract calls for overcoming obstacles, conducting clinical trials, establishing global regulatory norms and fostering collaboration between ophthalmologists and Artificial Intelligence experts. Overall, the article envisions Artificial Intelligence's imminent transformative impact on ocular and periocular cancer diagnosis.
在我们的文章中,我们探讨了人工智能和机器学习在眼肿瘤学中的变革潜力,重点关注眼附属器肿瘤的诊断和管理。该研究深入探讨了结膜黑色素瘤和结膜鳞状细胞癌等附属器疾病的复杂性,强调了近期的突破,如人工智能驱动的早期检测方法。在承认存在专业数据集稀缺和图像采集标准化问题等挑战的同时,该研究强调了患者令人鼓舞的接受度,这在黑色素瘤诊断研究中得到了体现。摘要呼吁克服障碍、开展临床试验、建立全球监管规范,并促进眼科医生与人工智能专家之间的合作。总体而言,本文设想了人工智能对眼部和眼周癌症诊断即将产生的变革性影响。