机器学习和视觉:推进糖尿病白内障管理的前沿
Najah K Mohammad1, Ibrahim A Rajab1, Rania H Al-Taie2
1Department of Ophthalmology, University of Baghdad, Baghdad, IRQ.
Cureus
|September 11, 2024
概括
机器学习 (ML) 提供了管理糖尿病白内障的新方法,改善了早期检测和治疗. 持续的研究和合作是克服挑战和提高患者护理的关键.
科学领域:
- 眼科医生 眼科 眼科
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 糖尿病白内障在患者护理中构成了重大挑战.
- 目前的管理方法需要一个整体的观点,强调氧化应激和代谢障碍.
- 机器学习 (ML) 为创新解决方案提供了潜力.
研究的目的:
- 综合审查ML在糖尿病白内障管理中的整合.
- 确定用于早期检测,诊断和治疗干预的新型ML方法.
- 为应对临床翻译挑战和伦理考虑.
主要方法:
- 通过PubMed和Scopus进行文献搜索.
- 专注于目前的创新,挑战,以及糖尿病白内障管理中的ML的未来方向.
- 探索最近和基础研究,以确定研究缺口.
主要成果:
- ML在眼科领域具有广泛的应用,包括治疗识别,白内障检测/分级以及手术结果的改善.
- 关键的挑战包括偏见的风险,人工智能作为诊断工具的担忧,以及法律法规.
- 氧化应激和代谢障碍是白内障发生的关键因素.
结论:
- ML有望在糖尿病白内障诊断,治疗和患者护理方面取得重大进展.
- 临床翻译和伦理考虑是很大的障碍.
- 持续的模型改进,跨学科的合作和扩展的研究对于最大限度地提高患者的结果至关重要.
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