Article record

人工智能驱动的阻塞性睡眠呼吸暂停诊断、内型分型与风险分层

Artificial Intelligence-Driven Diagnosis, Endotyping and Risk Stratification in Obstructive Sleep Apnea.

综述 Meta鼻科IF 5Q2

文献信息

PMID	42977358
原文	在 PubMed 查看原文 ↗
发表日期	2026
作者	Ghassan Alqenae 查看其他 3 位作者 Najib T Ayas；Aaron Boussina；Atul Malhotra
作者单位	Department of Medicine, Leon Judah Blackmore Sleep Disorders Program, UBC Hospital, University of British Columbia, Vancouver, Canada. 查看其他 2 条单位信息 Division of Biomedical Informatics, Department of Medicine, University of California, San Diego, La Jolla, CA, USA.；Department of Medicine, University of California, San Diego, La Jolla, CA, USA. Electronic address: amalhotra@health.ucsd.edu.
期刊	Sleep medicine clinics
SCI 分区	Q2
IF	5
研究类型	综述 Meta · 临床
所属专科	鼻科

中文摘要

睡眠相关检查中可用的多模态数据输入，使睡眠医学成为人工智能（AI）发挥重要影响的理想学科。使用AI辅助诊断OSA可缩短等待时间，并促成更早的诊断和治疗。大数据使AI能够对患者特征进行详细分析，并有助于对患者进行亚类划分。AI是一种重要工具，可用于增强睡眠专科医师的能力：改善工作流程、弥合症状出现与诊断之间的差距，并促进对患者采取精准医疗方法。

英文摘要

Multimodal data inputs available in sleep-related investigations positions sleep medicine as an ideal discipline for the impactful use of Artificial Intelligence (AI). Using AI to help diagnose OSA can reduce wait times and lead to earlier diagnosis and treatment. Big data can allow for detailed analysis of patient characteristics using AI and can aid in sub-categorizing patients. AI is an important tool that could be used to augment sleep providers to: improve workflow, bridge the gap between symptom onset and diagnosis, and facilitate a precision care approach to our patients.