机器学习用于静脉评估和伤口护理的应用:一篇评论
Miloš Madić1, Nikola Vitković1, Zoran Damnjanović2,3
1Department of Production and Information Technologies, Faculty of Mechanical Engineering, University of Niš, 18000 Niš, Serbia.
Diagnostics (Basel, Switzerland)
|February 13, 2026
概括
机器学习 (ML) 模型正在推进静脉的伤口护理. 本次审查分析了2001年至2025年的79项研究,总结了慢性伤口管理中的ML应用,益处和未来研究方向.
科学领域:
- 医疗信息学 医疗信息学
- 人工智能在医学中的应用
- 伤口护理研究 伤口护理研究
背景情况:
- 静脉伤护理在机器学习 (ML) 集成方面取得了重大进展.
- 对现有研究进行全面分析对于了解ML的影响至关重要.
研究的目的:
- 从2001年到2025年8月,系统地分析ML在静脉伤护理中的应用研究.
- 确定这一领域的趋势,好处,局限性和未来的研究机会.
主要方法:
- 在 Web of Science,Scopus 和 PubMed 上进行系统的文献搜索.
- 纳入/排除标准用于导出79项相关研究进行分析.
- 在静脉治疗中对ML模型应用的元分析和详细检查.
主要成果:
- 对79项研究的分析揭示了ML模型在静脉创伤管理中的多种应用.
- 确定了医疗保健系统和患者的好处,以及ML模型的局限性.
- 讨论包括当前的趋势,机会和现有研究的局限性.
结论:
- ML模型具有显著的潜力,可以提高静脉的伤口护理.
- 需要进一步的研究来解决局限性问题,并探索慢性伤口管理中的更广泛应用.
- 本综述为ML和伤口护理研究人员提供了有价值的见解.
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