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Deep Learning for Diagnosis and Classification of Obstructive Sleep Apnea: A Nasal Airflow-Based Multi-Resolution Residual Network.
Yue, Huijun; Lin, Yu; Wu, Yitao; Wang, Yongquan; Li, Yun; Guo, Xueqin; Huang, Ying; Wen, Weiping; Zhao, Gansen; Pang, Xiongwen; Lei, Wenbin.
Affiliation
  • Yue H; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Lin Y; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Wu Y; School of Computer Science, South China Normal University, Guangzhou, 510631, People's Republic of China.
  • Wang Y; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Li Y; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Guo X; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Huang Y; Guangdong Province Traditional Chinese Medical Hospital, Guangzhou, 510000, People's Republic of China.
  • Wen W; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
  • Zhao G; School of Computer Science, South China Normal University, Guangzhou, 510631, People's Republic of China.
  • Pang X; School of Computer Science, South China Normal University, Guangzhou, 510631, People's Republic of China.
  • Lei W; Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510080, People's Republic of China.
Nat Sci Sleep ; 13: 361-373, 2021.
Article de En | MEDLINE | ID: mdl-33737850

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Diagnostic_studies / Prognostic_studies Langue: En Journal: Nat Sci Sleep Année: 2021 Type de document: Article Pays de publication: Nouvelle-Zélande

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Type d'étude: Diagnostic_studies / Prognostic_studies Langue: En Journal: Nat Sci Sleep Année: 2021 Type de document: Article Pays de publication: Nouvelle-Zélande