C3-PO: A Convolutional Neural Network for COVID Onset Prediction from Cough Sounds
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-53311-2_26
Reference25 articles.
1. Andreu-Perez, J., et al.: A generic deep learning based cough analysis system from clinically validated samples for point-of-need Covid-19 test and severity levels. IEEE Trans. Serv. Comput. 15(3), 1220–1232 (2021). https://doi.org/10.1109/TSC.2021.3061402
2. Ashby, A.E., Meister, J.A., Soldar, G., Nguyen, K.A.: A novel cough audio segmentation framework for covid-19 detection. In: Proceedings of the Symposium on Open Data and Knowledge for a Post-Pandemic Era ODAK22, UK, pp. 1–8 (2022). https://doi.org/10.14236/ewic/ODAK22.1
3. Bhattacharya, D., et al.: Coswara: a respiratory sounds and symptoms dataset for remote screening of SARS-COV-2 infection. Sci. Data 10(1), 397 (2023)
4. Duan, H., Wei, Y., Liu, P., Yin, H.: A novel ensemble framework based on k-means and resampling for imbalanced data. Appl. Sci. 10(5), 1684 (2020)
5. Furtado, A., da Purificação, C.A.C., Badaró, R., Nascimento, E.G.S.: A light deep learning algorithm for CT diagnosis of COVID-19 Pneumonia. Diagnostics 12(7), 1527 (2022). https://doi.org/10.3390/diagnostics12071527
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