基于数字图像分析的糖尿病脚查的人工智能:系统性审查
Ni Kadek Indah Sunar Anggreni1, Heri Kristianto1, Dian Handayani2
1Nursing Department, Faculty of Health Sciences, Brawijaya University, Malang, Indonesia.
Journal of diabetes science and technology
|February 17, 2025
概括
人工智能 (AI) 显示出使用数字图像分析进行糖尿病脚查的巨大潜力. 人工智能模型,特别是人工神经网络 (ANN),可以准确地检测并发症,改善早期诊断和患者的治疗结果.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 糖尿病并发症 糖尿病并发症
背景情况:
- 糖尿病足部并发症需要早期检测才能有效管理.
- 使用数字图像分析的人工智能 (AI) 提供了一种非侵入性查方法.
- 本系统性审查的重点是开发用于糖尿病脚查的AI模型.
研究的目的:
- 系统地审查有关AI模型开发用于糖尿病脚查的研究.
- 确定人工智能在分析数字足部图像的有效性,以便早期检测并发症.
主要方法:
- 在2018-2023年间发表的文章的系统审查来自PubMed,ProQuest和ScienceDirect.
- 纳入标准适用于最初识别的2214篇文章,导致9项研究被选中.
- 使用QUADAS进行质量评估;通过NVivo.com进行数据提取和分析.
主要成果:
- 热成像 (脚温度图) 和脚部温度模式是关键数据来源.
- 深度学习方法,包括人工神经网络 (ANN) 和卷积神经网络 (CNN),是普遍存在的.
- 一个ANN模型在分类斑点类型方面达到97.5%的准确性,显示出高性能.
结论:
- 人工智能具有显著的潜力,可以提高糖尿病脚查的准确性和效率.
- 未来的研究应该涉及临床适用性,伦理考虑和数据安全.
- 开发全面的数据集对于在糖尿病足护理中推进人工智能至关重要.
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