| 段晓晔,张丽娜,满富丽,等.人工智能在骨质疏松症诊疗中的应用进展[J].中国临床保健杂志,2025,28(5):631-635. |
| 人工智能在骨质疏松症诊疗中的应用进展 |
| Advances in artificial intelligence for osteoporosis diagnosis and treatment |
| 投稿时间：2025-06-29 |
| DOI：10.3969/J.issn.1672-6790.2025.05.009 |
| 中文关键词: 骨质疏松 人工智能 危险性评估 诊断技术和方法 综述 |
| 英文关键词: Osteoporosis Artificial intelligence Risk assessment Diagnostic techniques and procedures Review 〖FL |
| 基金项目:首都卫生发展科研专项(2024-1-4053)；中国医学科学院医学与健康科技创新工程项目(2021-I2M-1-050) |
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| 摘要点击次数: 38 |
| 全文下载次数: 25 |
| 中文摘要: |
| 近年来,人工智能(AI)技术为骨质疏松的预测、诊断和治疗带来了革命性突破。AI在医学影像分析中展现出卓越能力,能够通过深度学习算法精准识别骨密度变化和微结构异常,提高早期诊断率。基于大数据的风险预测模型可整合临床、遗传和生活方式等多维度信息,实现个体化风险评估。AI辅助的个性化治疗方案进一步优化了临床决策,同时进行动态随访,实现患者风险分层、远程监护、个体化干预的全程管理。然而,AI技术的应用仍面临数据质量、算法可解释性及临床转化等挑战。本文综述了AI在骨质疏松领域的应用现状,分析其优势与局限性,并展望未来发展方向,以期为临床实践和科研提供参考。 |
| 英文摘要: |
| Recently,artificial intelligence (AI) technology has brought transformative breakthroughs to the diagnosis,prediction,and treatment of osteoporosis.AI excels in medical imaging analysis,where deep learning algorithms enable precise identification of bone mineral density (BMD) changes and microstructural abnormalities,thereby enhancing early diagnosis rates.Big data-driven risk prediction models integrate multidimensional information—including clinical,genetic,and lifestyle factors—to achieve individualized risk assessment.AI-assisted personalized treatment plans further optimize clinical decision-making,while dynamic follow-up systems support comprehensive patient management through risk stratification,remote monitoring,and tailored interventions.Nevertheless,challenges remain in data quality,algorithm interpretability,and clinical translation.This review examines the current applications of AI in osteoporosis,analyzes its advantages and limitations,and explores future directions to inform clinical practice and research. |
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