在肺高血压 (PH) 中对人工智能 (AI) 应用进行全面审查
Sogol Attaripour Esfahani1, Nima Baba Ali1, Juan M Farina1
1Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, AZ 85054, USA.
人工智能 (AI) 在改善肺高血压 (PH) 诊断和管理方面表现有前途. 人工智能应用可以提高准确性,效率和风险分层,以改善PH护理中的患者结果.
科学领域:
- 医疗信息学 医疗信息学
- 心脏病学 心脏病学
- 人工智能在医学中的应用
背景情况:
- 肺高血压 (PH) 在诊断和管理方面存在重大挑战,影响患者的发病率和死亡率.
- 目前用于PH的传统方法往往导致诊断延迟和低于最佳治疗.
- 人工智能 (AI),包括机器学习 (ML) 和深度学习 (DL),为PH护理提供了一个新的范式.
研究的目的:
- 系统地审查和分析AI在肺高血压的诊断,分类和预后中的应用.
- 探索AI如何提高PH检测和风险分层的准确性和效率.
- 评估AI在优化PH患者治疗策略方面的潜力.
主要方法:
- 在PubMed,Scopus和Web of Science中进行了系统的文献搜索,以寻找PH中的AI研究.
- 在500多篇初步文章中,共选出了45项相关研究.
- 用预测模型风险偏差评估工具 (PROBAST) 评估偏差风险.
主要成果:
- 人工智能应用显示出提高PH诊断的准确性和效率的潜力.
- 人工智能可以提高肺高血压疾病的分类和预后.
- 人工智能驱动的风险分层对优化治疗计划和改善患者结果具有前景.
结论:
- 人工智能为彻底改变肺高血压的管理提供了一个重要的机会.
- 为了克服现有的挑战,需要对人工智能工具进行进一步的研究和改进.
- 人工智能有可能大大改善肺高血压护理患者的治疗结果.
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