Artificial intelligence and machine learning a new frontier in the diagnosis of ocular adnexal tumors: A review.

IF 2.3 Q2 MEDICINE, GENERAL & INTERNAL
SAGE Open Medicine Pub Date : 2024-08-27 eCollection Date: 2024-01-01 DOI:10.1177/20503121241274197
Qirat Qurban, Lorraine Cassidy
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引用次数: 0

Abstract

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.

人工智能和机器学习是眼部附件肿瘤诊断的新领域:综述。
在我们的文章中,我们探讨了人工智能和机器学习在眼部肿瘤学中的变革潜力,重点关注眼部附件肿瘤的诊断和管理。该研究深入探讨了结膜黑色素瘤和鳞状结膜癌等附件疾病的复杂性,强调了最近取得的突破,如人工智能驱动的早期检测方法。该研究承认存在专业数据集稀缺和图像采集标准化问题等挑战,但强调患者接受度令人鼓舞,黑色素瘤诊断研究就证明了这一点。摘要呼吁克服障碍,开展临床试验,建立全球监管规范,促进眼科医生和人工智能专家之间的合作。总之,文章展望了人工智能即将对眼部和眼周癌症诊断产生的变革性影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
SAGE Open Medicine
SAGE Open Medicine MEDICINE, GENERAL & INTERNAL-
CiteScore
3.50
自引率
4.30%
发文量
289
审稿时长
12 weeks
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