A predictive algorithm to identify genes that discriminate individuals with fibromyalgia syndrome diagnosis from healthy controls.

Lukkahatai, Nada; Walitt, Brian; Deandrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Saligan, Leorey N

Lukkahatai, Nada; Walitt, Brian; Deandrés-Galiana, Enrique J; Fernández-Martínez, Juan Luis; Saligan, Leorey N.

Afiliação

Lukkahatai N; Acute and Chronic Care, Johns Hopkins School of Nursing, Baltimore, MD, USA, nada.lukkahatai@jhu.edu.
Walitt B; Symptoms Biology Unit, National Institute of Nursing Research (NINR), Bethesda, MD, USA.
Deandrés-Galiana EJ; Group of Inverse Problems, Optimization and Machine Learning, Applied Mathematics, University of Oviedo, Oviedo, Spain.
Fernández-Martínez JL; Group of Inverse Problems, Optimization and Machine Learning, Applied Mathematics, University of Oviedo, Oviedo, Spain.
Saligan LN; Symptoms Biology Unit, National Institute of Nursing Research (NINR), Bethesda, MD, USA.

J Pain Res ; 11: 2981-2990, 2018.

Article em En | MEDLINE | ID: mdl-30538537

Palavras-chave

chronic pain; machine learning; medically unexplained symptoms; microarray

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: J Pain Res Ano de publicação: 2018 Tipo de documento: Article

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