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Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study.
Fagherazzi, Guy; Zhang, Lu; Aguayo, Gloria; Pastore, Jessica; Goetzinger, Catherine; Fischer, Aurélie; Malisoux, Laurent; Samouda, Hanen; Bohn, Torsten; Ruiz-Castell, Maria; Huiart, Laetitia.
Afiliación
  • Fagherazzi G; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg. guy.fagherazzi@lih.lu.
  • Zhang L; Center of Epidemiology and Population Health UMR 1018, Inserm, Gustave Roussy Institute, Paris South - Paris Saclay University, Villejuif, France. guy.fagherazzi@lih.lu.
  • Aguayo G; Quantitative Biology Unit, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Pastore J; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Goetzinger C; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Fischer A; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Malisoux L; University of Luxembourg, 2, avenue de l'Université, 4365, Esch-sur-Alzette, Luxembourg.
  • Samouda H; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Bohn T; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Ruiz-Castell M; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
  • Huiart L; Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.
Sci Rep ; 11(1): 16056, 2021 08 06.
Article en En | MEDLINE | ID: mdl-34362963
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Índice de Masa Corporal / Aprendizaje Automático / Aprendizaje Automático Supervisado / Enfermedades Metabólicas / Obesidad Tipo de estudio: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Luxemburgo Pais de publicación: Reino Unido
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Enfermedades Cardiovasculares / Índice de Masa Corporal / Aprendizaje Automático / Aprendizaje Automático Supervisado / Enfermedades Metabólicas / Obesidad Tipo de estudio: Etiology_studies / Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged País/Región como asunto: Europa Idioma: En Revista: Sci Rep Año: 2021 Tipo del documento: Article País de afiliación: Luxemburgo Pais de publicación: Reino Unido