Your browser doesn't support javascript.
loading
ACSN: Attention capsule sampling network for diagnosing COVID-19 based on chest CT scans.
Wen, Cuihong; Liu, Shaowu; Liu, Shuai; Heidari, Ali Asghar; Hijji, Mohammad; Zarco, Carmen; Muhammad, Khan.
Afiliação
  • Wen C; College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, China; State Key Laboratory for Turbulence and Complex Systems, Department of Advanced Manufacturing and Robotics, College of Engineering, Peking University, Beijing, 100871, China.
  • Liu S; College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, China.
  • Liu S; College of Information Science and Engineering, Hunan Normal University, Changsha, 410081, China; School of Educational Science, Hunan Normal University, Changsha, 410081, China; Key Laboratory of Big Data Research and Application for Basic Education, Hunan Normal University, Changsha, 410081, China
  • Heidari AA; School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, 1439957131, Iran. Electronic address: as_heidari@ut.ac.ir.
  • Hijji M; Faculty of Computers and Information Technology (FCIT), University of Tabuk, Tabuk, 47711, Saudi Arabia.
  • Zarco C; Andalusian Research Institute in Data Science and Computational Intelligence (DaSCI), University of Granada (UGR), Spain.
  • Muhammad K; Visual Analytics for Knowledge Laboratory (VIS2KNOW Lab), Department of Applied AI, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, 03063, South Korea. Electronic address: khan.muhammad@ieee.org.
Comput Biol Med ; 153: 106338, 2023 02.
Article em En | MEDLINE | ID: mdl-36640529
Assuntos
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: COVID-19 Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Humans Idioma: En Revista: Comput Biol Med Ano de publicação: 2023 Tipo de documento: Article