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    Machine learning-aided screening of COVID-19 in Lung Ultrasound images.

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    Undergraduate dissertation (2.846Mb)
    Date
    2022-01-22
    Author
    Mirembe, Betty
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    Abstract
    In this project, the transfer learning technique was exploited on several deep learning algorithms to classify COVID-19 in Lung Ultrasound images. Training and preliminary testing of the algorithms was performed with the use of a data set of 792 images that contained several distinct features that are indicative of either of the classes of interest i.e. COVID-19 and healthy. Particularly the VGG-16 framework provided outstanding optimal results with a remarkable accuracy of 97.5 percent and a recall of 95.7 percent. The astounding success rate makes the model a very useful advisory screening approach in this field of medical imaging to aid further diagnosis of COVID-19.
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    http://hdl.handle.net/20.500.12281/12061
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