Explainable COVID-19 detection using fractal dimension and vision transformer with Grad-CAM on cough sounds

Pandemic 2020 emergencies/diseases/novel-coronavirus-2019 https://www.who.int/.

Sengur, 2020, Investigation of the relationships of the students’ academic level and gender with Covid-19 based anxiety and protective behaviors: A data mining approach, Turkish J. Sci. Technol., 15, 93

Lan, 2020, Positive RT-PCR test results in patients recovered from COVID-19, Jama Network, 323, 1502

Alqudaihi, 2021, Cough sound detection and diagnosis using artificial intelligence techniques: challenges and opportunities, IEEE Access, 9, 102327, 10.1109/ACCESS.2021.3097559

Pahar, 2021, COVID-19 Cough Classification using machine learning and global smartphone recordings, Comput Biol Med, 135, 1

Laguarta, 2020, COVID-19 artificial intelligence diagnosis using only cough recordings, IEEE Open J Eng Med Biol, 1, 275, 10.1109/OJEMB.2020.3026928

Alsabek M B, Shahin I, Hassan A. Studying the similarity of COVID-19 sounds based on correlation analysis of MFCC. In: International Conference on Communications, Computing, Cybersecurity, and Informatics (CCCI) 2008 November 3 (pp. 1-5). IEEE.

Sharma N, Krishnan P, Kumar R, Ramoji S, et al. Coswara-A database of breathing, cough, and voice sounds for COVID-19 diagnosis. In: Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech 2020 October 25 (pp. 4811-4815).ISCA.

Mouawad, 2021, Robust detection of COVID-19 in cough sounds, SN Computer Science, 2, 1

Erdoğan, 2021, COVID-19 detection with traditional and deep features on cough acoustic signals, Comput Biol Med, 136, 1

Despotovic, 2021, Detection of COVID-19 from voice, cough and breathing patterns: dataset and preliminary results, Comput Biol Med, 138, 1

Tena, 2022, Automated detection of COVID-19 cough, Biomed. Signal Process. Control, 71, 1

Kobat, 1962, Automated COVID-19 and heart failure detection using DNA pattern technique with cough sounds, Diagnostics, 2021, 1

Chang, 2021, CovNet: A transfer learning framework for automatic COVID-19 detection from crowd-sourced cough sounds, Frontiers in Digital Health, 3, 1

Chowdhury, 2022, Machine learning for detecting COVID-19 from cough sounds: An ensemble-based MCDM method, Comput Biol Med, 145, 1

Islam, 2022, A study of using cough sounds and deep neural networks for the early detection of COVID-19, Biomed Eng Adv, 3, 1

Hamdi, 2022, Attention-based hybrid CNN-LSTM and spectral data augmentation for COVID-19 diagnosis from cough sound, J Intellig Informat Syst, 1

Manshouri, 2022, Identifying COVID-19 by using spectral analysis of cough recordings: a distinctive classification study, Cogn Neurodyn, 16, 239, 10.1007/s11571-021-09695-w

Lee, 2022, Deep learning based cough detection camera using enhanced features, Expert Syst Appl, 206, 1

Dang T, Han J, Xia T, Spathis D, Bondareva E, et al. Exploring longitudinal cough, breath, and voice data for COVID-19 progression prediction via sequential deep learning: model development and validation. J Med Intern Res 2022: 24(6), e37004; 1-14.

Rahman, 2022, QUCoughScope: An intelligent application to Detect COVID-19 patients using cough and breath sounds, Diagnostics, 12(4), 920, 1

Ren, 2022, The acoustic dissection of cough: diving into machine listening-based COVID-19 analysis and detection, J. Voice, 36, 1

Sharan, 2022, Automated discrimination of cough in audio recordings: A scoping review, Frontiers in Signal Processing, 2, 1

Gabaldón-Figueira, 2022, Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence, ERJ Open Research, 8, 1, 10.1183/23120541.00053-2022

Andreu-Perez, 2021, 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, 1220, 10.1109/TSC.2021.3061402

Zealouk, 2021, Analysis of COVID-19 resulting cough using formants and automatic speech recognition system, J. Voice, 36, 1

YAMNet, YAMNet neural network, 2021 https://github.com/tensorflow/models/tree/master/research/ audioset/yamnet.

Atila, 2021, Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition, Appl Acoust, 182, 1

Howard, 2017, MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications. Cornell University arXiv, Comput Vis Patt Recogn, 1704, 1

Gemmeke J F, Ellis D P W, Freedman D, Jansen A, Lawrence W, et al. Audio Set: An ontology and human-labeled dataset for audio events. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2017 March 5 (pp. 776-780).IEEE.

Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Llion Jones, Gomez A N, et al. Attention is all you need. In: 31st Conference on Neural Information Processing Systems (NIPS) 2017 December 4 (pp. 1-15). Curran Associates Inc.

Katz, 1985, Fractal sandstone pores: implications for conductivity and pore formation, Phys Rev Lett, 54, 1325, 10.1103/PhysRevLett.54.1325

Higuchi, 1988, Approach to an irregular time series on the basis of the fractal theory, Phys D: Nonlinear Phenom, 31, 277, 10.1016/0167-2789(88)90081-4

Petrosian A. Kolmogorov complexity of finite sequences and recognition of different preictal EEG patterns. In: Proceedings Eighth IEEE Symposium on Computer-Based Medical Systems 1995 June 9 (pp. 212-217). IEEE.

Castiglioni, 2010, Letter to the Editor: What is wrong in Katz's method? Comments on:“ A note on fractal dimensions of biomedical waveforms, Comput Biol Med, 40, 950, 10.1016/j.compbiomed.2010.10.001

Orlandic, 2021, The COUGHVID crowdsourcing dataset, a corpus for the study of large-scale cough analysis algorithms, Sci Data, 8, 1, 10.1038/s41597-021-00937-4

Chaudhari, 2011, Virufy: Global applicability of crowdsourced and clinical datasets for AI detection of COVID-19 from cough, Cornell University arXiv, Sound, 13320, 1

Sharma N, Krishnan P, Kumar R, Ramoji S, Chetupalli S R, et al. Coswara-A database of breathing, cough, and voice sounds for COVID-19 diagnosis. In: Proceedings Interspeech 2020 October 25 (pp. 4811-4815). Interspeech.

Hugging Face, Fine-Tune ViT for image classification with transformers, 2021, https://huggingface.co /blog/fine-tune-vit.

Deniz, 2018, Transfer learning based histopathologic image classification for breast cancer detection, Health Informat Sci Syst, 6, 1

Kadiroğlu Z, Şengür A, Deniz E. Classification of histopathological breast cancer images with low level texture features. In: International Engineering and Natural Sciences Conference (IENSC) 2018, November 14 (pp. 1765-1772). INESEG.

Selvaraju R R, Cogswell M, Das A, Vedantam R, Parikh D, Batra D. Grad-Cam: Visual explanations from deep networks via gradient-based localization. In: Proceedings of the IEEE international conference on computer vision (ICCV) 2017 October 22 (pp. 618-626). IEEE.

Jahmunah, 2022, Explainable detection of myocardial infarction using deep learning models with Grad-CAM technique on ECG signals, Comput Biol Med, 146, 1

Son, 2022, COVID-19 diagnosis from crowdsourced cough sound data, Appl Sci, 12, 1, 10.3390/app12041795

Xue H, Salim F D. Exploring self-supervised representation ensembles for covid-19 cough classification. In:Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining2021 August 14 (pp. 1944-1952). KDD.

Soltanian, 2022, Covid-19 recognition from cough sounds using lightweight separable-quadratic convolutional network, Biomed Signal Process Control, 72, 1