对于管理阻塞性肺部疾病患者的呼吸系统临床医生来说,人工智能的解密化
Joana Antão1,2,3,4, Jeroen de Mast5, Alda Marques1,2
1Lab3R - Respiratory Research and Rehabilitation Laboratory, School of Health Sciences, University of Aveiro (ESSUA), Aveiro, Portugal.
Expert review of respiratory medicine
|January 25, 2024
概括
人工智能 (AI) 可以优化喘和慢性阻塞性肺病 (COPD) 的诊断和治疗. 这次审查弥合了临床医生和数据科学家之间的知识差距,以鼓励人工智能采用以获得更好的患者结果.
科学领域:
- 呼吸系统药物 呼吸系统药物
- 医疗信息学医学信息学
- 人工智能的人工智能是人工智能.
背景情况:
- 喘和COPD是全球主要的健康问题,负有重大负担.
- 目前的诊断和治疗因疾病的复杂性和异质性而面临挑战.
- 人工智能 (AI) 具有增强呼吸系统疾病临床决策的潜力.
研究的目的:
- 弥合呼吸系统临床医生和数据科学家之间关于AI的知识差距.
- 解释AI方法及其在喘和COPD诊断和治疗中的价值.
- 鼓励更广泛地部署人工智能来管理慢性呼吸系统疾病.
主要方法:
- 这篇叙事评论解释了基本的AI和机器学习概念.
- 它概述了构建AI模型的过程.
- 提供了AI在喘和COPD护理中的应用示例.
主要成果:
- 人工智能可以优化喘和COPD的诊断和治疗策略.
- 人工智能模型可以预测恶化风险,疾病进展和死亡率.
- 了解AI方法对于其有效实施至关重要.
结论:
- 机器学习可以促进对喘和COPD的理解,从而导致个性化治疗.
- 进一步的研究和验证对于具有临床意义和可泛化的AI模型至关重要.
- 解决知识差距是释放人工智能在呼吸护理方面的潜力的关键.
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