Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies

Version 1 : Received: 15 March 2023 / Approved: 16 March 2023 / Online: 16 March 2023 (02:53:04 CET)
Version 2 : Received: 21 May 2023 / Approved: 23 May 2023 / Online: 23 May 2023 (03:42:44 CEST)
Version 3 : Received: 23 May 2023 / Approved: 24 May 2023 / Online: 25 May 2023 (02:41:35 CEST)
Version 4 : Received: 5 November 2024 / Approved: 7 November 2024 / Online: 8 November 2024 (11:57:41 CET)

How to cite: Morshed, A.; Al Shihab, A.; Jahin, M. A.; Al Nahian, M. J.; Sarker, M. M. H.; Ibne Wadud, M. S.; Uddin, M. I.; Siraji, M. I.; Anjum, N.; Shristy, S. R.; Rahman, T.; Khatun, M.; Javed, F. I.; Dewan, M. R.; Hossain, M.; Sultana, R.; Chakma, R.; Emon, S. B.; Islam, T.; Hussain, M. Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies. Preprints 2023, 2023030296. https://doi.org/10.20944/preprints202303.0296.v1 Morshed, A.; Al Shihab, A.; Jahin, M. A.; Al Nahian, M. J.; Sarker, M. M. H.; Ibne Wadud, M. S.; Uddin, M. I.; Siraji, M. I.; Anjum, N.; Shristy, S. R.; Rahman, T.; Khatun, M.; Javed, F. I.; Dewan, M. R.; Hossain, M.; Sultana, R.; Chakma, R.; Emon, S. B.; Islam, T.; Hussain, M. Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies. Preprints 2023, 2023030296. https://doi.org/10.20944/preprints202303.0296.v1

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MDPI and ACS Style

Morshed, A.; Al Shihab, A.; Jahin, M. A.; Al Nahian, M. J.; Sarker, M. M. H.; Ibne Wadud, M. S.; Uddin, M. I.; Siraji, M. I.; Anjum, N.; Shristy, S. R.; Rahman, T.; Khatun, M.; Javed, F. I.; Dewan, M. R.; Hossain, M.; Sultana, R.; Chakma, R.; Emon, S. B.; Islam, T.; Hussain, M. Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies. Preprints 2023, 2023030296. https://doi.org/10.20944/preprints202303.0296.v1

APA Style

Morshed, A., Al Shihab, A., Jahin, M. A., Al Nahian, M. J., Sarker, M. M. H., Ibne Wadud, M. S., Uddin, M. I., Siraji, M. I., Anjum, N., Shristy, S. R., Rahman, T., Khatun, M., Javed, F. I., Dewan, M. R., Hossain, M., Sultana, R., Chakma, R., Emon, S. B., Islam, T., & Hussain, M. (2023). Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies. Preprints. https://doi.org/10.20944/preprints202303.0296.v1

Chicago/Turabian Style

Morshed, A., Towhidul Islam and Mohammad Hussain. 2023 "Ultrasound-Based AI for COVID-19 Detection: A Comprehensive Review of Public and Private Lung Ultrasound Datasets and Studies" Preprints. https://doi.org/10.20944/preprints202303.0296.v1

Abstract

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

Keywords

COVID-19, Deep learning, Artificial Intelligence, Ultrasound, Review

Subject

Computer Science and Mathematics, Artificial Intelligence and Machine Learning

Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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