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About Automated Diagnosis of COVID-19 With Limited Poste
This document summarizes research on using deep learning models to automatically diagnose COVID-19 from limited chest X-ray images. The researchers fine-tuned several state-of-the-art deep neural networks using techniques like random oversampling and weighted class loss functions to address the challenge of limited COVID-19 sample sizes in available datasets. They evaluated the models' performance on binary and multi-class classification of chest X-rays as normal, COVID-19, or pneumonia cases. Experimental results found the NASNetLarge model generally performed best, though performance depended on the specific scenario. The researchers also provided visual explanations of model classifications to illustrate how COVID-19 is perceived in chest X-rays.
Detailed Information
| Author: | ['YULIA'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 17 |
| Language: | English |
| Format: | |
| Price: | FREE |
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