作者：禅与计算机程序设计艺术
1.简介
Deep learning has revolutionized the field of computer vision and image processing by enabling machine learning models to learn from large datasets without hand-crafted features or labeled data. In this paper, we will explore deep learning based object recognition techniques for applications in healthcare industry such as diagnosis and prognosis of diseases using chest X-ray images. We have reviewed a few state-of-the-art algorithms including convolutional neural networks (CNN), residual networks, and long short-term memory networks (LSTM). Moreover, we have developed several customized methods on top of these traditional architectures to enhance their performance on specific disease detection tasks. Our experimental results show that our proposed methods outperform standard CNNs and LSTM architectures significantly.
The purpose of this article is to present recent advances in deep learning based approaches to medical i