Applying a novel approach to scoping review incorporating artificial intelligence: mapping the natural history of gonorrhoea.

Whelan, Jane; Ghoniem, Mohammad; Médoc, Nicolas; Apicella, Mike; Beck, Ekkehard

Whelan, Jane; Ghoniem, Mohammad; Médoc, Nicolas; Apicella, Mike; Beck, Ekkehard.

Afiliación

Whelan J; GSK, Amsterdam, The Netherlands. whelanjane@hotmail.com.
Ghoniem M; Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg.
Médoc N; Luxembourg Institute of Science and Technology, Esch-sur-Alzette, Luxembourg.
Apicella M; University of Iowa, Iowa City, USA.
Beck E; GSK, Wavre, Belgium.

BMC Med Res Methodol ; 21(1): 183, 2021 09 06.

Article en En | MEDLINE | ID: mdl-34488645

Asunto(s)

Inteligencia Artificial; Gonorrea; Gonorrea/diagnóstico; Gonorrea/epidemiología; Humanos; Recién Nacido; MEDLINE; Tamizaje Masivo

Palabras clave

Artificial intelligence; Clinical outcomes; Co-clustering; Gonorrhoea; Health problems; N. gonorrhoeae; Natural history; Natural language processing; Scoping review; Visual text mining

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Inteligencia Artificial / Gonorrea Tipo de estudio: Diagnostic_studies / Guideline / Prognostic_studies / Screening_studies / Systematic_reviews Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2021 Tipo del documento: Article

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