Art

J-GLOBAL ID：202102279143915856   Reference number：21A2033386

Deep Learning Approaches for Detecting Pneumonia in COVID-19 Patients by Analyzing Chest X-Ray Images

胸部X線画像分析によるCOVID-19患者の肺炎検出のための深層学習アプローチ【JST・京大機械翻訳】

Author (8)： Hasan M. D. Kamrul (Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka-1229, Bangladesh) ,  Ahmed Sakil (Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka-1229, Bangladesh) ,  Abdullah Z. M. Ekram (Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka-1229, Bangladesh) ,  Monirujjaman Khan Mohammad (Department of Electrical and Computer Engineering, North South University, Bashundhara, Dhaka-1229, Bangladesh) ,  Anand Divya (Department of Computer Science and Engineering, Lovely Professional University, Punjab-144411, Phagwara, India) ,  Singh Aman (Department of Computer Science and Engineering, Lovely Professional University, Punjab-144411, Phagwara, India) ,  AlZain Mohammad (Department of Information Technology, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif 21944, Saudi Arabia) ,  Masud Mehedi (Department of Computer Science, College of Computers and Information Technology, Taif University, P. O. Box 11099, Taif 21944, Saudi Arabia)
Material： Mathematical Problems in Engineering (Web)
Volume： 2021  Page： Null  Publication year： 2021 
JST Material Number： U7803A  ISSN： 1024-123X  Document type： Article
Article type： 原著論文  Country of issue： United Kingdom (GBR)  Language： ENGLISH (EN)

Abstract/Point： The COVID-19 pandemic has wrea...

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Thesaurus term： optimization ,  *pneumonia ,  human(primates) ,  adult(person) ,  two dimension ,  complication
Semi thesaurus term： *胸部X線撮影 ,  特異性 ,  Python ,  *胸部X線画像 ,  学習ツール ,  *深層学習 ,  畳込みニューラルネットワーク , 【Automatic Indexing@JST】

JST classification (2)： Respiratory system diagnosis  (GI02000S) ,  Medical image processing  (JE04020T)

Reference (36)：

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Terms in the title (6)： 胸部X線画像 ,  分析 ,  COVID-19 ,  患者 ,  肺炎 ,  深層学習