Cholesterol Contributes to Risk, Severity, and Machine Learning-Driven Diagnosis of Lyme Disease.

Forrest, Iain S; O'Neal, Anya J; Pedra, Joao H F; Do, Ron

Forrest, Iain S; O'Neal, Anya J; Pedra, Joao H F; Do, Ron.

Afiliación

Forrest IS; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
O'Neal AJ; Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Pedra JHF; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Do R; Department of Microbiology and Immunology, University of Maryland School of Medicine, Baltimore, Maryland, USA.

Clin Infect Dis ; 77(6): 839-847, 2023 09 18.

Article en En | MEDLINE | ID: mdl-37227948

Asunto(s)

Hipercolesterolemia; Enfermedad de Lyme; Humanos; Enfermedad de Lyme/diagnóstico; Enfermedad de Lyme/epidemiología; Colesterol; Pronóstico; Aprendizaje Automático

Palabras clave

Lyme disease; cholesterol; exome sequencing; machine learning

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Texto completo: 1 Base de datos: MEDLINE Asunto principal: Enfermedad de Lyme / Hipercolesterolemia Tipo de estudio: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Clin Infect Dis Asunto de la revista: DOENCAS TRANSMISSIVEIS Año: 2023 Tipo del documento: Article

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