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Chest X-ray analysis empowered with deep learning: A systematic review by Dulani Meedeniya; Hashara Kumarasinghe; Shammi Kolonne; Chamodi Fernando; Isabel De la Torre Díez; Gonçalo Marques is a Computer Science article available to read on EtoBox.

What is Chest X-ray analysis empowered with deep learning: A systematic review about?

Chest radiographs are widely used in the medical domain and at present, chest X-radiation particularly plays an important role in the diagnosis of medical conditions such as pneumonia and COVID-19 disease. The recent developments of deep learning techniques led to a promising performance in medical image classification and prediction tasks. With the availability of chest X-ray datasets and emerging trends in data engineering techniques, there is a growth in recent related publications. Recently, there have been only a few survey papers that addressed chest X-ray classification using deep learning techniques. However, they lack the analysis of the trends of recent studies. This systematic review paper explores and provides a comprehensive analysis of the related studies that have used deep learning techniques to analyze chest X-ray images. We present the state-of-the-art deep learning based pneumonia and COVID-19 detection solutions, trends in recent studies, publicly available datasets, guidance to follow a deep learning process, challenges and potential future research directions in this domain. The discoveries and the conclusions of the reviewed work have been organized in a way

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Author

Dulani Meedeniya; Hashara Kumarasinghe; Shammi Kolonne; Chamodi Fernando; Isabel De la Torre Díez; Gonçalo Marques

Publisher

Elsevier BV

Published

2022

Language

EN

Field

Computer Science (Physical Sciences)