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- W4312881373 abstract "In 2019, the outbreak of a new coronavirus spread rapidly around the world. The use of medical image-assisted diagnosis for suspected patients can provide a more accurate and rapid picture of the disease. The earlier the diagnosis is made and the earlier the patient is treated, the lower the likelihood of virus transmission. This paper reviews current research advances in the processing of lung CT images in combination with promising deep learning, including image segmentation, recognition, and classification, and provides a comparison in a tabular format, hoping to provide inspiration for their future development." @default.
- W4312881373 created "2023-01-05" @default.
- W4312881373 creator A5041076952 @default.
- W4312881373 date "2022-10-26" @default.
- W4312881373 modified "2023-10-16" @default.
- W4312881373 title "A Review of Deep Learning-Based Methods for the Diagnosis and Prediction of COVID-19" @default.
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- W4312881373 doi "https://doi.org/10.4018/ijpch.311444" @default.
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