Research and Practice of X-ray Chest Film Disease Classification based on DenseNet

机译：基于DenseNet的X线胸片疾病分类研究与实践

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X-ray examination, commonly used to examine chest diseases, is a common medical examination in patients’ physical examination. In this paper, the disease information is extracted based on the X-ray chest film report, and the disease types are classified by using DenseNet. The highest AUC can reach more than 0.935, the positive recall rate is about 0.82, and the negative recall rate is about 0.92, which has a good effect.

机译：X射线检查常用于检查胸部疾病，是患者体检中的常见体检。本文基于X射线胸膜报告提取疾病信息，通过使用DENSENET来分类疾病类型。最高AUC可达到0.935以上，正回忆速率约为0.82，负召回率约为0.92，具有良好的效果。

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《International Conference on Artificial Intelligence and Education》|2020年|241-244|共4页
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LIANG Bing-jin; Yin Jian; Lin Yan-jun; Pan Liang; Lin Guo-xiong;
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Training; Hafnium; Diseases; Data models; Conferences; Artificial intelligence; Annotations;

机译：培训; H;疾病;数据模型;会议;人工智能;注释;

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专利

1. Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases [J] . Arun Sharma, Sheeba Rani, Dinesh Gupta International journal of biomedical imaging . 2020,第3期

机译：基于人工智能的胸部X射线图像分类，进入Covid-19和其他传染病
2. A new modular neural network approach with fuzzy response integration for lung disease classification based on multiple objective feature optimization in chest X-ray images [J] . Varela-Santos Sergio, Melin Patricia Expert systems with applications . 2021,第Apra期

机译：一种新的模块神经网络方法，基于胸X射线图像多目标特征优化的肺病分类模糊响应集成
3. SDFN: Segmentation-based deep fusion network for thoracic disease classification in chest X-ray images [J] . Han Liu, Lei Wang, Yong Nan, Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society . 2019,第期

机译：SDFN：基于分段的胸部疾病分类的深度融合网络胸部X射线图像中的分类
4. Densely Connected Convolutional Networks (DenseNet) for Diagnosing Coronavirus Disease (COVID-19) from Chest X-ray Imaging [C] . Hamed Tabrizchi, Amir Mosavi, Zoltan Vamossy, IEEE International Symposium on Medical Measurements and Applications . 2021

机译：密集连接卷积网络（DENSENET），用于诊断胸X射线成像的冠状病毒疾病（Covid-19）
5. Uncertainty Quantification for Deep Neural Networks in Chest X-Ray Image Classification [D] . Sahin, Serhat. 2018

机译：胸部X射线图像分类中深神经网络的不确定性量化
6. Artificial Intelligence-Based Classification of Chest X-Ray Images into COVID-19 and Other Infectious Diseases [O] . Arun Sharma, Sheeba Rani, Dinesh Gupta 2020

机译：基于人工智能的胸部X射线图像分类进入Covid-19和其他传染病
7. Reliable Learning with PDE-Based CNNs and DenseNets for Detecting COVID-19, Pneumonia, and Tuberculosis from Chest X-Ray Images [O] . Anca Nicoleta Marginean, Delia Doris Muntean, George Adrian Muntean, 2021

机译：可靠地学习基于PDE的CNN和DENSENETS，用于检测Covid-19，肺炎和胸部X射线图像的结核病

Research and Practice of X-ray Chest Film Disease Classification based on DenseNet

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