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Using CNN-XGBoost Deep Networks for COVID-19 Detection in Chest X-ray Images

Ahmed Mabrouk Fangoh, Sahar Selim
2020 2020 15th International Conference on Computer Engineering and Systems (ICCES)  

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At the time of writing, the COVID-19 pandemic is one of the lead causes of death worldwide and has caused significant changes to everyone's lives. While a vaccine is still unavailable, early screenings and detection of the disease can significantly help in managing the healthcare system's capacity as well as allow radiologists and clinicians better assign their priorities. With deep learning's rapid advancements over the last few years, its application in solving this issue is only natural.
more » ... paper aims to outline the works of a few major developments in the field of using deep learning to classify COVID-19 cases, illustrating common techniques and issues faced. Following this, a deep learning architecture is proposed and tested, then compared to the findings of the mentioned papers.
doi:10.1109/icces51560.2020.9334600 fatcat:32tgd2og6jdt7kdabjzswmxhkq
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Ahmed Mabrouk Fangoh, Sahar Selim. "Using CNN-XGBoost Deep Networks for COVID-19 Detection in Chest X-ray Images." 2020 15th International Conference on Computer Engineering and Systems (ICCES) (2020)