Comparison and Validation of Deep Learning Models for the Diagnosis of Pneumonia
المؤلفون المشاركون
Yue, Zhenjia
Ma, Liangping
Zhang, Runfeng
المصدر
Computational Intelligence and Neuroscience
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-09-18
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
As a respiratory infection, pneumonia has gained great attention from countries all over the world for its strong spreading and relatively high mortality.
For pneumonia, early detection and treatment will reduce its mortality rate significantly.
Currently, X-ray diagnosis is recognized as a relatively effective method.
The visual analysis of a patient’s X-ray chest radiograph by an experienced doctor takes about 5 to 15 minutes.
When cases are concentrated, this will undoubtedly put tremendous pressure on the doctor’s clinical diagnosis.
Therefore, relying on the naked eye of the imaging doctor has very low efficiency.
Hence, the use of artificial intelligence for clinical image diagnosis of pneumonia is a necessary thing.
In addition, artificial intelligence recognition is very fast, and the convolutional neural networks (CNNs) have achieved better performance than human beings in terms of image identification.
Therefore, we used the dataset which has chest X-ray images for classification made available by Kaggle with a total of 5216 train and 624 test images, with 2 classes as normal and pneumonia.
We performed studies using five mainstream network algorithms to classify these diseases in the dataset and compared the results, from which we improved MobileNet’s network structure and achieved a higher accuracy rate than other methods.
Furthermore, the improved MobileNet’s network could also extend to other areas for application.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Yue, Zhenjia& Ma, Liangping& Zhang, Runfeng. 2020. Comparison and Validation of Deep Learning Models for the Diagnosis of Pneumonia. Computational Intelligence and Neuroscience،Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1138938
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Yue, Zhenjia…[et al.]. Comparison and Validation of Deep Learning Models for the Diagnosis of Pneumonia. Computational Intelligence and Neuroscience No. 2020 (2020), pp.1-8.
https://search.emarefa.net/detail/BIM-1138938
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Yue, Zhenjia& Ma, Liangping& Zhang, Runfeng. Comparison and Validation of Deep Learning Models for the Diagnosis of Pneumonia. Computational Intelligence and Neuroscience. 2020. Vol. 2020, no. 2020, pp.1-8.
https://search.emarefa.net/detail/BIM-1138938
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138938
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر