Identifying Profiles and Symptoms of Patients With Long COVID in France: Data Mining Infodemiology Study Based on Social Media.

Déguilhem, Amélia; Malaab, Joelle; Talmatkadi, Manissa; Renner, Simon; Foulquié, Pierre; Fagherazzi, Guy; Loussikian, Paul; Marty, Tom; Mebarki, Adel; Texier, Nathalie; Schuck, Stephane

Déguilhem, Amélia; Malaab, Joelle; Talmatkadi, Manissa; Renner, Simon; Foulquié, Pierre; Fagherazzi, Guy; Loussikian, Paul; Marty, Tom; Mebarki, Adel; Texier, Nathalie; Schuck, Stephane.

Afiliación

Déguilhem A; Kap Code Paris France.
Malaab J; Kap Code Paris France.
Talmatkadi M; Kap Code Paris France.
Renner S; Kap Code Paris France.
Foulquié P; Kap Code Paris France.
Fagherazzi G; Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health Strassen Luxembourg.
Loussikian P; Kap Code Paris France.
Marty T; Kap Code Paris France.
Mebarki A; Kap Code Paris France.
Texier N; Kap Code Paris France.
Schuck S; Kap Code Paris France.

JMIR Infodemiology ; 2(2): e39849, 2022.

Article en En | MEDLINE | ID: mdl-36447795

Palabras clave

COVID-19; Long Haulers; condition; content; difficulties encountered; discussion; infodemiology; infodemiology study; long COVID; patient-reported outcomes; persistent; social media; symptoms; topics

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: JMIR Infodemiology Año: 2022 Tipo del documento: Article