Automatic Classification of Diseases From X-Ray Images Using Xception Deep Convolution Neural Networks

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Author(s): Venkatesan R. (SASTRA University (Deemed), India)and Umamaheswari P. (SASTRA University (Deemed), India)
Copyright: 2023
Pages: 15
Source title: Using Multimedia Systems, Tools, and Technologies for Smart Healthcare Services
Source Author(s)/Editor(s): Amit Kumar Tyagi (National Institute of Fashion Technology, New Delhi, India)
DOI: 10.4018/978-1-6684-5741-2.ch011

Keywords: Media & Communications / Medical Information Science Reference / Medical Technologies / Multimedia Technology

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Abstract

The growth of artificial intelligence (AI) and deep learning in recent years has been played vital role scientific and research related field. The influence of AI can be seen and felt in many fields today. One of the most important applications of AI is in the field of medicine. Across the globe, many radiological societies are exploring medical image analysis (MIA) with the application of AI techniques. The inclusion and deployment of AI in medical imaging have changed the way of interpretation and diagnosis drastically. This experiment was aimed to classify multiple diseases from the X-ray images using Xception deep convolutional neural networks (XDCNN). The chest X-ray images were trained in the Xception network. The system classified 18 diseases based on ground truths and the accuracy rate was calculated.

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Automatic Classification of Diseases From X-Ray Images Using Xception Deep Convolution Neural Networks

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