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BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data.
Rahman, Tawsifur; Chowdhury, Muhammad E H; Khandakar, Amith; Mahbub, Zaid Bin; Hossain, Md Sakib Abrar; Alhatou, Abraham; Abdalla, Eynas; Muthiyal, Sreekumar; Islam, Khandaker Farzana; Kashem, Saad Bin Abul; Khan, Muhammad Salman; Zughaier, Susu M; Hossain, Maqsud.
Afiliação
  • Rahman T; Department of Electrical Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Chowdhury MEH; Department of Electrical Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Khandakar A; Department of Electrical Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Mahbub ZB; Department of Physics and Mathematics, North South University, Dhaka, 1229 Bangladesh.
  • Hossain MSA; NSU Genome Research Institute (NGRI), North South University, Dhaka, 1229 Bangladesh.
  • Alhatou A; Department of Biology, University of South Carolina (USC), Columbia, SC 29208 USA.
  • Abdalla E; Anesthesia Department, Hamad General Hospital, P.O. Box 3050, Doha, Qatar.
  • Muthiyal S; Department of Radiology, Hamad General Hospital, P.O. Box 3050, Doha, Qatar.
  • Islam KF; Department of Electrical Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Kashem SBA; Department of Computer Science, AFG College with the University of Aberdeen, Doha, Qatar.
  • Khan MS; Department of Electrical Engineering, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Zughaier SM; Department of Basic Medical Sciences, College of Medicine, QU Health, Qatar University, P.O. Box 2713, Doha, Qatar.
  • Hossain M; NSU Genome Research Institute (NGRI), North South University, Dhaka, 1229 Bangladesh.
Neural Comput Appl ; : 1-23, 2023 May 04.
Article em En | MEDLINE | ID: mdl-37362565
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article