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人工智能应用在慢性阻塞性肺病管理方面的进展

Mingyu Wang¹, Luhan Li¹, Min Feng¹

¹The First Affiliated Hospital of Dalian Medical University, Dalian, China.

Frontiers in medicine

|October 30, 2025

概括

人工智能 (AI) 为治疗慢性阻塞性肺病 (COPD) 提供了先进的解决方案. 人工智能工具,包括机器学习,有助于早期预测,诊断,治疗和预后,减少医疗保健负担.

科学领域:

医疗信息学医疗信息学
呼吸系统医学呼吸系统医学
人工智能的人工智能

背景情况:

慢性阻塞性肺病 (COPD) 由于发病率和死亡率高,给全球健康带来了重大挑战.
目前对COPD的管理策略在解决疾病的复杂性和患者异质性方面存在局限性.

研究的目的:

审查人工智能 (AI) 在COPD综合管理中的技术应用和临床价值.
探索AI在整个COPD疾病连续性的作用,从预测到预后.
讨论COPD研究和临床实践中人工智能的当前挑战和未来方向.

主要方法:

对包括机器学习 (ML) 和深度学习 (DL) 在COPD中的AI应用程序的审查.
分析人工智能与多式联网数据,放射学,生物信息学和多式联网数据的整合.
检查人工智能驱动的工具,用于风险预测,诊断,治疗改进和预后评估.

主要成果:

人工智能在早期风险预测,精确诊断和COPD个性化治疗方面显示出显著的潜力.
机器学习模型有效评估急性恶化和并发症风险.
人工智能与生物信息学和多态学相结合,为COPD管理建立了一个智能框架.

结论:

人工智能提供创新的,个性化的解决方案,以减轻COPD的医疗负担.
进一步开发和整合AI对于推进COPD护理至关重要.
人工智能为改善COPD的临床实践和研究成果提供了一个有希望的途径.

关键词:

人工智能的人工智能是人工智能.慢性阻塞性肺病慢性阻塞性肺病深度神经网络是一个神经网络.机器学习是机器学习.多式多样化的多式模式

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