Literature DB >> 33001844

Can routine laboratory variables predict survival in COVID-19? An artificial neural network-based approach.

Alejandro Santos-Lozano1,2, Fernando Calvo-Boyero3, Ana López-Jiménez3, Cecilia Cueto-Felgueroso3, Adrián Castillo-García4, Pedro L Valenzuela5, Joaquín Arenas2, Alejandro Lucia2,6,7, Miguel A Martín2,8.   

Abstract

Entities:  

Keywords:  biochemistry; coronavirus; hematology; mortality

Mesh：

Year:  2020        PMID： 33001844     DOI： 10.1515/cclm-2020-0730

Source DB:  PubMed          Journal:  Clin Chem Lab Med        ISSN： 1434-6621            Impact factor:   3.694


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  3 in total

1.  Hematological abnormalities in immunosuppressed patients with COVID-19: Evidence from a single center. A cross sectional study.

Authors:  Annesi Giacaman; Wolfrang Henriquez; Guillermo Tolosa; Aurora Prado; Roxana Jerez; Yenny Reveco; Carlos Martínez; Carlos Baumert; Belén Rodríguez; Basty Sanhueza; Juan José Orellana; Jaime Inostroza
Journal:  Int Immunopharmacol       Date:  2022-05-17       Impact factor: 5.714

2.  The prediction of the lifetime of the new coronavirus in the USA using mathematical models.

Authors:  K Selvakumar; S Lokesh
Journal:  Soft comput       Date:  2021-03-10       Impact factor: 3.732

3.  Role of red blood cell distribution width, as a prognostic indicator in COVID-19: A systematic review and meta-analysis.

Authors:  Soumya Sarkar; Sundara Kannan; Puneet Khanna; Akhil Kant Singh
Journal:  Rev Med Virol       Date:  2021-06-06       Impact factor: 11.043
  3 in total

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