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In this paper, we propose a deep convolutional neural network (CNN) based method for thorax disease diagnosis. We firstly align the images by matching the ...
In this paper, we propose a deep convolutional neural network. (CNN) based method for thorax disease diagnosis. We firstly align the images by matching the ...
In this paper, we demonstrate the feasibility of classifying the chest pathologies in chest X-rays using conventional and deep learning approaches.
A deep convolutional neural network (CNN) based method for thorax disease diagnosis is proposed, which firstly align the images by matching the interest ...
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Oct 22, 2024 · In this paper, we propose a deep convolutional neural network (CNN) based method for thorax disease diagnosis. We firstly align the images by ...
Dec 15, 2023 · This paper presents a novel and promising approach, namely DCNN-GRU, for improving the detection and classification of lung abnormalities.
Missing: Thorax | Show results with:Thorax
Nov 30, 2024 · In this study, we developed a lightweight and rapid convolutional neural network (CNN) architecture for chest X-ray images; it primarily ...
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Through this survey paper, researchers may be able to gain an overall and systematic knowledge of deep learning applications in medical thoracic images.
Mar 26, 2023 · Our dataset can be used to train models with high diagnostic accuracy for predicting the likelihood of 14 different diseases in abnormal chest radiographs.