骨质疏松症查工具的现状和困境:一个叙事审查
Yuji Zhang1, Ming Ma1, Cong Tian1
1Department of Orthopaedics, The Second Hospital of Lanzhou University, China; Gansu Orthopaedic Clinical Medical Research Centre, China; Gansu Intelligent Orthopaedic Industry Technology Centre, China.
Clinical nutrition ESPEN
|October 12, 2024
概括
与人工智能 (AI) 集成的X射线成像显示,与传统工具相比,骨质疏松症查的精度更高. 这项技术为各种人群提供了更好的可访问性和个性化的评估,特别是在资源有限的环境中.
科学领域:
- 医疗成像医学成像
- 人工智能的人工智能
- 骨质疏松症查 骨质疏松症查
背景情况:
- 现有的骨质疏松症查工具 (例如,OSTA,SCORE) 在可访问性,临床翻译性和可用性方面面临挑战.
- 这些传统方法往往在查结果的解释和在不同人群中的适用性方面存在局限性.
研究的目的:
- 审查当前骨质疏松症查工具的优点和局限性.
- 探索人工智能集成X射线成像的潜力,以提高骨质疏松症查准确度和更广泛的人口适用性.
- 确定优化现有选方法和克服当前困境的策略.
主要方法:
- 在PubMed,Web of Science和CNKI数据库 (2000-2023) 中进行了全面的文献搜索.
- 包括的研究评估了骨质疏松症查工具,医学成像中的AI,以及AI在临床环境中的实施.
- 选择标准侧重于研究常见的查工具 (OSTA,SCORE,ABONE,OSIRIS) 和人工智能驱动的成像在各种人群中,并指出优点和缺点.
主要成果:
- 与传统的骨质疏松症查工具相比,AI集成的X射线成像显示出更高的准确性和个性化的评估能力.
- 人工智能系统有效地结合了复杂的临床数据,提高了早期检测骨密度损失的灵敏度和特异性,特别是在复杂的患者资料中.
- 人工智能技术显示出通过移动设备和远程诊断在资源有限的环境中有效应用的潜力.
结论:
- 人工智能集成的X射线成像代表了骨质疏松症查的重大进步,提供了更准确和更适应的解决方案.
- 该技术的复杂数据集成能力和多样化的人口应用对多样化和资源有限的环境具有前景.
- 进一步的研究是必要的,以充分实现人工智能的潜力,提高查的可访问性和有效性,特别是对于服务不足的人群.
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