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Correction: Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study.
Aguayo, Gloria A; Zhang, Lu; Vaillant, Michel; Ngari, Moses; Perquin, Magali; Moran, Valerie; Huiart, Laetitia; Krüger, Rejko; Azuaje, Francisco; Ferdynus, Cyril; Fagherazzi, Guy.
Afiliación
  • Aguayo GA; Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg. gloria.aguayo@lih.lu.
  • Zhang L; Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Vaillant M; CompetenceCenter for Methodology and Statistics, Translational Medicine Operations Hub, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Ngari M; CompetenceCenter for Methodology and Statistics, Translational Medicine Operations Hub, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Perquin M; KEMRI/ Wellcome Trust Research Programme, Kilifi, Kenya.
  • Moran V; Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Huiart L; Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Krüger R; Living Conditions Department, Luxembourg Institute of Socio-Economic Research, Esch-Sur-Alzette, Luxembourg.
  • Azuaje F; Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
  • Ferdynus C; LCSB, Luxembourg Centre for System Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg.
  • Fagherazzi G; Parkinson Research Clinic, Centre Hospitalier de Luxembourg, Luxembourg, Luxembourg.
BMC Med Res Methodol ; 23(1): 32, 2023 Jan 31.
Article en En | MEDLINE | ID: mdl-36721092
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Luxemburgo
Texto completo
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: BMC Med Res Methodol Asunto de la revista: MEDICINA Año: 2023 Tipo del documento: Article País de afiliación: Luxemburgo