Abstract
The continued and rapid global spread of COVID-19 is taking a heavy toll on the global economy and human health, which has attracted the attention of professionals in various fields. Controlling the spread of this disease and reducing the threat to human life is of paramount importance. There are no clinically effective drugs for this disease. However, research on deep learning-based diagnostic systems for COVID-19 has yielded significant results and is expected to be an essential weapon in the fight against COVID-19 in the future. This paper provides a brief summary and evaluation of 15 studies on deep learning-based COVID-19 diagnostics, covering a total of 13 common pre-trained models and nine custom deep learning models in the COVID-19 dataset, and discusses the current challenges and future trends in this category of research. This paper aims to help healthcare professionals and researchers understand the advances in deep learning techniques for COVID-19 diagnosis to assist them in conducting relevant research to stop the further spread of COVID-19.
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Wang, W. (2022). A Short Survey on Deep Learning Models for Covid-19 Detection Based on Chest CT and X-ray Images. In: Wang, S., Zhang, Z., Xu, Y. (eds) IoT and Big Data Technologies for Health Care. IoTCare 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 415. Springer, Cham. https://doi.org/10.1007/978-3-030-94182-6_39
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DOI: https://doi.org/10.1007/978-3-030-94182-6_39
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