人工智能在慢性鼻炎中的作用:一个范围审查
Nicola M Pereira1, Sarah J Wie1, Karena Zhao1
1Department of Otolaryngology-Head and Neck Surgery, Weill Cornell Medicine, New York, New York, USA.
International forum of allergy & rhinology
|December 11, 2025
概括
人工智能 (AI) 在诊断和管理慢性鼻炎 (CRS) 方面表现有前途. 虽然目前的人工智能应用专注于诊断和预后,但对于手术规划和临床工具需要进一步研究.
科学领域:
- 耳鼻喉科 耳鼻喉科 耳鼻喉科
- 医疗信息学 医疗信息学
- 人工智能的人工智能
背景情况:
- 人工智能 (AI) 越来越多地用于诊断和管理慢性疾病.
- 慢性鼻炎 (CRS) 为人工智能驱动的耳鼻喉学优化提供了重大机会.
- 在CRS诊断和管理中的AI应用正在迅速发展.
研究的目的:
- 在慢性鼻炎 (CRS) 中对AI应用进行范围审查.
- 为了确定当前的趋势,研究差距和AI在CRS中的未来机会.
- 在CRS诊断和管理中绘制AI的地图.
主要方法:
- 从创立到2024年4月,在多个数据库 (Ovid MEDLINE,EMBASE,Web of Science,Cochrane Library) 进行了全面的文献搜索.
- 如果它们使用人工智能进行CRS诊断或管理,则包括研究,但不包括非英语,2003年之前的急性鼻炎和儿科研究.
- 从573个选记录中选择了49项研究进行定性分析.
主要成果:
- 深度学习,神经网络和卷积神经网络是常见的AI技术.
- 大多数研究 (55%) 专注于用于CRS诊断的AI,而其他研究则关注预后 (29%) 和治疗反应 (12%).
- 人工智能模型被训练在各种变量上,包括CT成像,乙素计数,临床数据和细胞因子,使用分类和回归指标评估性能.
结论:
- 人工智能是一个有希望的,尽管处于早期阶段,用于管理慢性鼻炎 (CRS) 的工具.
- 目前的人工智能应用在CRS诊断,亚型和预后方面取得了进展.
- 需要进一步的研究来探索AI在手术规划,经济评估和CRS交互式临床工具中的实用性.
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