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用于快速检测气道狭窄和喘鸣的变压器。 (注:这里“transformers”根据语境可能不是常规意义的变压器,也许是一种特定的检测设备等,具体含义需结合更多背景信息确定,仅按字面翻译)

Transformers for rapid detection of airway stenosis and stridor.

作者信息

Anibal James, Doctor Rebecca, Boyer Micah, Newberry Karlee, De Santiago Iris, Awan Shaheen, Abdel-Aty Yassmeen, Dion Gregory, Daoud Veronica, Huth Hannah, Watts Stephanie, Wood Bradford J, Clifton David, Gelbard Alexander, Powell Maria, Toghranegar Jamie, Bensoussan Yael

机构信息

Center for Interventional Oncology, NIH Clinical Center, National Institutes of Health, Bethesda, USA.

Computational Health Informatics Lab, Institute of Biomedical Engineering, University of Oxford, Oxford, England.

出版信息

Sci Rep. 2025 May 2;15(1):15394. doi: 10.1038/s41598-025-99369-y.

Abstract

Upper airway stenosis is a potentially life-threatening condition involving the narrowing of the airway. In more severe cases, airway stenosis may be accompanied by stridor, a type of disordered breathing caused by turbulent airflow. Patients with airway stenosis have a higher risk of airway failure and additional precautions must be taken before medical interventions like intubation. However, stenosis and stridor are often misdiagnosed as other respiratory conditions like asthma/wheezing, worsening outcomes. This report presents a unified dataset containing recorded breathing tasks from patients with stridor and airway stenosis. Customized transformer-based models were also trained to perform stenosis and stridor detection tasks using low-cost data from multiple acoustic prompts recorded on common devices. These methods achieved AUC scores of 0.875 for stenosis detection and 0.864 for stridor detection, demonstrating the potential to add value as screening tools in real-world clinical workflows, particularly in high-volume settings like emergency departments.

摘要

上气道狭窄是一种潜在的危及生命的疾病,涉及气道变窄。在更严重的情况下,气道狭窄可能伴有喘鸣,这是一种由气流紊乱引起的呼吸障碍。气道狭窄患者发生气道衰竭的风险更高,在进行诸如插管等医疗干预之前必须采取额外的预防措施。然而,狭窄和喘鸣常常被误诊为哮喘/喘息等其他呼吸系统疾病,从而使病情恶化。本报告展示了一个统一的数据集,其中包含了患有喘鸣和气道狭窄患者的呼吸任务记录。还训练了基于定制变压器的模型,以使用在普通设备上记录的多个声学提示的低成本数据来执行狭窄和喘鸣检测任务。这些方法在狭窄检测方面的AUC得分为0.875,在喘鸣检测方面的AUC得分为0.864,这表明它们有潜力作为现实世界临床工作流程中的筛查工具增加价值,特别是在急诊科等高流量环境中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/44bb/12048665/671ed84c3075/41598_2025_99369_Fig1_HTML.jpg

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