标题
The Use of Audio Signals for Detecting COVID-19: A Systematic Review
作者
关键词
-
出版物
SENSORS
Volume 22, Issue 21, Pages 8114
出版商
MDPI AG
发表日期
2022-10-24
DOI
10.3390/s22218114
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Detection of COVID-19 in smartphone-based breathing recordings: A pre-screening deep learning tool
- (2022) Mohanad Alkhodari et al. PLoS One
- How social distancing, mobility, and preventive policies affect COVID-19 outcomes: Big data-driven evidence from the District of Columbia-Maryland-Virginia (DMV) megaregion
- (2022) Jina Mahmoudi et al. PLoS One
- COVID-19 Diagnosis from Crowdsourced Cough Sound Data
- (2022) Myoung-Jin Son et al. Applied Sciences-Basel
- VECTOR: An algorithm for the detection of COVID-19 pneumonia from velcro-like lung sounds
- (2022) Fabrizio Pancaldi et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Past and Trends in Cough Sound Acquisition, Automatic Detection and Automatic Classification: A Comparative Review
- (2022) Antoine Serrurier et al. SENSORS
- Challenges and Opportunities of Deep Learning for Cough-Based COVID-19 Diagnosis: A Scoping Review
- (2022) Syrine Ghrabli et al. Diagnostics
- Projected COVID-19 epidemic in the United States in the context of the effectiveness of a potential vaccine and implications for social distancing and face mask use
- (2021) Mingwang Shen et al. VACCINE
- Identifying COVID-19 by using spectral analysis of cough recordings: a distinctive classification study
- (2021) Negin Melek Manshouri Cognitive Neurodynamics
- COVID-19 cough classification using machine learning and global smartphone recordings
- (2021) Madhurananda Pahar et al. COMPUTERS IN BIOLOGY AND MEDICINE
- COVID-19 detection with traditional and deep features on cough acoustic signals
- (2021) Yunus Emre Erdoğan et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters
- (2021) Amir Vahedian-azimi et al. JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
- Diagnosis of COVID-19 and non-COVID-19 patients by classifying only a single cough sound
- (2021) Mesut Melek NEURAL COMPUTING & APPLICATIONS
- Controlling COVID-19 via test-trace-quarantine
- (2021) Cliff C. Kerr et al. Nature Communications
- The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms
- (2021) Lara Orlandic et al. Scientific Data
- Automated detection of COVID-19 cough
- (2021) Alberto Tena et al. Biomedical Signal Processing and Control
- COVID-19 detection in cough, breath and speech using deep transfer learning and bottleneck features
- (2021) Madhurananda Pahar et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Diagnosing COVID-19: The Disease and Tools for Detection
- (2020) Buddhisha Udugama et al. ACS Nano
- Mild or Moderate Covid-19
- (2020) Rajesh T. Gandhi et al. NEW ENGLAND JOURNAL OF MEDICINE
- Mechanisms of SARS-CoV-2 transmission and pathogenesis
- (2020) Andrew G. Harrison et al. TRENDS IN IMMUNOLOGY
- Deep Convolutional Neural Networks and Data Augmentation for Environmental Sound Classification
- (2017) Justin Salamon et al. IEEE SIGNAL PROCESSING LETTERS
- Mechanics of human voice production and control
- (2016) Zhaoyan Zhang JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA
- Effects of age on the amplitude, frequency and perceived quality of voice
- (2015) Catherine L. Lortie et al. AGE
- The Role of Balanced Training and Testing Data Sets for Binary Classifiers in Bioinformatics
- (2013) Qiong Wei et al. PLoS One
- Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement
- (2010) David Moher et al. International Journal of Surgery
- Automatic Detection System for Cough Sounds as a Symptom of Abnormal Health Condition
- (2009) Sung-Hwan Shin et al. IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More