A critical analysis of COVID-19 research literature: Text mining approach.

Zengul, Ferhat D; Zengul, Ayse G; Mugavero, Michael J; Oner, Nurettin; Ozaydin, Bunyamin; Delen, Dursun; Willig, James H; Kennedy, Kierstin C; Cimino, James

Zengul, Ferhat D; Zengul, Ayse G; Mugavero, Michael J; Oner, Nurettin; Ozaydin, Bunyamin; Delen, Dursun; Willig, James H; Kennedy, Kierstin C; Cimino, James.

Afiliação

Zengul FD; Department of Health Services Administration, The University of Alabama at Birmingham, USA.
Zengul AG; School of Engineering- Center for Integrated Systems, The University of Alabama at Birmingham, USA.
Mugavero MJ; Department of Nutrition, The University of Alabama at Birmingham, USA.
Oner N; Department of Medicine, Division of Infectious Diseases, The University of Alabama at Birmingham, USA.
Ozaydin B; Department of Health Services Administration, The University of Alabama at Birmingham, USA.
Delen D; Department of Health Services Administration, The University of Alabama at Birmingham, USA.
Willig JH; School of Engineering- Center for Integrated Systems, The University of Alabama at Birmingham, USA.
Kennedy KC; Department of Management Science, School of Business, Ibn Haldun University, Istanbul, Turkey.
Cimino J; Center for Health Systems Innovation, Spears School of Business, Oklahoma State University, Stillwater, OK, USA.

Intell Based Med ; 5: 100036, 2021.

Article em En | MEDLINE | ID: mdl-34179855

Palavras-chave

COVID-19; Natural language processing; SARS COV-2; Text mining; Topic modeling

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Intell Based Med Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo

Adicionar na Minha BVS

Imprimir

XML

PubMed Links

Buscar no Google