Potential applications of artificial intelligence in image analysis in cornea diseases: a review.

IF 5.4 3区材料科学 Q2 CHEMISTRY, PHYSICAL

ACS Applied Energy Materials Pub Date : 2024-03-07 DOI:10.1186/s40662-024-00376-3

Kai Yuan Tey, Ezekiel Ze Ken Cheong, Marcus Ang

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Abstract

Artificial intelligence (AI) is an emerging field which could make an intelligent healthcare model a reality and has been garnering traction in the field of medicine, with promising results. There have been recent developments in machine learning and/or deep learning algorithms for applications in ophthalmology-primarily for diabetic retinopathy, and age-related macular degeneration. However, AI research in the field of cornea diseases is relatively new. Algorithms have been described to assist clinicians in diagnosis or detection of cornea conditions such as keratoconus, infectious keratitis and dry eye disease. AI may also be used for segmentation and analysis of cornea imaging or tomography as an adjunctive tool. Despite the potential advantages that these new technologies offer, there are challenges that need to be addressed before they can be integrated into clinical practice. In this review, we aim to summarize current literature and provide an update regarding recent advances in AI technologies pertaining to corneal diseases, and its potential future application, in particular pertaining to image analysis.

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人工智能在角膜疾病图像分析中的潜在应用：综述。

人工智能（AI）是一个新兴领域，它可以使智能医疗模式成为现实，并在医学领域获得了广泛的关注，取得了可喜的成果。最近，机器学习和/或深度学习算法在眼科领域的应用有了新的发展--主要用于糖尿病视网膜病变和老年性黄斑变性。然而，角膜疾病领域的人工智能研究相对较新。已有算法用于协助临床医生诊断或检测角膜疾病，如角膜炎、感染性角膜炎和干眼症。作为一种辅助工具，人工智能还可用于角膜成像或断层扫描的分割和分析。尽管这些新技术具有潜在的优势，但在将其融入临床实践之前，还需要应对一些挑战。在这篇综述中，我们旨在总结当前的文献，并提供有关角膜疾病的人工智能技术最新进展及其未来的潜在应用，特别是在图像分析方面。

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

ACS Applied Energy Materials Materials Science-Materials Chemistry

CiteScore

10.30

自引率

6.20%

发文量

1368

期刊介绍： ACS Applied Energy Materials is an interdisciplinary journal publishing original research covering all aspects of materials, engineering, chemistry, physics and biology relevant to energy conversion and storage. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrate knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important energy applications.