Challenges and Opportunities in Deploying COVID-19 Cough AI Systems.
作者信息
Khanzada Amil, Hegde Siddhi, Sreeram Shreya, Bower Grace, Wang William, Mediratta Rishi P, Meister Kara D, Rameau Anaïs
机构信息
College of Engineering, University of California, Berkeley, California.
K.V.G. Medical College and Hospital, Sullia, Karnataka, India.
出版信息
J Voice. 2021 Nov;35(6):811-812. doi: 10.1016/j.jvoice.2021.08.009. Epub 2021 Sep 7.
Abstract
摘要
相似文献
1
Challenges and Opportunities in Deploying COVID-19 Cough AI Systems.部署新冠咳嗽人工智能系统中的挑战与机遇
J Voice. 2021 Nov;35(6):811-812. doi: 10.1016/j.jvoice.2021.08.009. Epub 2021 Sep 7.
2
Limitations of the Cough Sound-Based COVID-19 Diagnosis Artificial Intelligence Model and its Future Direction: Longitudinal Observation Study.基于咳嗽声音的新冠病毒肺炎诊断人工智能模型的局限性及其未来方向：纵向观察研究
J Med Internet Res. 2024 Feb 6;26:e51640. doi: 10.2196/51640.
3
Screening COVID-19 by Swaasa AI platform using cough sounds: a cross-sectional study.使用 Swaasa AI 平台对 COVID-19 进行筛查：一项横断面研究。
Sci Rep. 2023 Oct 25;13(1):18284. doi: 10.1038/s41598-023-45104-4.
4
Targeting Infectious Coronavirus Disease 2019 (COVID-19) with Artificial Intelligence (AI) Applications: Evidence Based Opinion.利用人工智能（AI）应用针对2019年传染性冠状病毒病（COVID-19）：基于证据的观点。
Infect Disord Drug Targets. 2021;21(4):475-477. doi: 10.2174/1871526520666200622144857.
5
Bias and privacy in AI's cough-based COVID-19 recognition - Authors' reply.人工智能基于咳嗽的新冠肺炎识别中的偏差与隐私——作者回复
Lancet Digit Health. 2021 Dec;3(12):e761. doi: 10.1016/S2589-7500(21)00233-8.
6
Detection of COVID-19 from voice, cough and breathing patterns: Dataset and preliminary results.从声音、咳嗽和呼吸模式中检测新冠病毒：数据集与初步结果
Comput Biol Med. 2021 Nov;138:104944. doi: 10.1016/j.compbiomed.2021.104944. Epub 2021 Oct 13.
7
Artificial intelligence approach fighting COVID-19 with repurposing drugs.人工智能方法通过药物再利用抗击 COVID-19。
Biomed J. 2020 Aug;43(4):355-362. doi: 10.1016/j.bj.2020.05.001. Epub 2020 May 15.
8
Application of an Artificial Intelligence Trilogy to Accelerate Processing of Suspected Patients With SARS-CoV-2 at a Smart Quarantine Station: Observational Study.应用人工智能三部曲在智能检疫站加速新型冠状病毒肺炎疑似患者的处理：观察性研究
J Med Internet Res. 2020 Oct 14;22(10):e19878. doi: 10.2196/19878.
9
Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning.胸腔床旁超声：SARS-CoV-2 的未来人工智能和机器学习数据仓库。
Surg Innov. 2021 Apr;28(2):214-219. doi: 10.1177/15533506211018671. Epub 2021 May 7.
10
[Application of AI Technology in Diagnosis and Treatment of COVID-19].[人工智能技术在新型冠状病毒肺炎诊疗中的应用]
Zhongguo Yi Liao Qi Xie Za Zhi. 2021 Jul 30;45(4):372-375. doi: 10.3969/j.issn.1671-7104.2021.04.004.
引用本文的文献
1
Detection of disease on nasal breath sound by new lightweight architecture: Using COVID-19 as an example.利用新型轻量级架构通过鼻腔呼吸声检测疾病：以新冠病毒病为例
Digit Health. 2025 May 28;11:20552076251339284. doi: 10.1177/20552076251339284. eCollection 2025 Jan-Dec.
2
Blazing the trail for innovative tuberculosis diagnostics.开拓结核病诊断创新之路。
Infection. 2024 Feb;52(1):29-42. doi: 10.1007/s15010-023-02135-3. Epub 2023 Nov 30.
3
Cough Sounds in Screening and Diagnostics: A Scoping Review.咳嗽声在筛查和诊断中的应用：范围综述。
Laryngoscope. 2024 Mar;134(3):1023-1031. doi: 10.1002/lary.31042. Epub 2023 Sep 6.
4
Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System.考虑基于声学的 COVID-19 筛查系统在实际部署中的注意事项和挑战。
Sensors (Basel). 2022 Dec 6;22(23):9530. doi: 10.3390/s22239530.
Zotero 插件