Identifying Patients With Hypoglycemia Using Natural Language Processing: Systematic Literature Review.

Zheng, Yaguang; Dickson, Victoria Vaughan; Blecker, Saul; Ng, Jason M; Rice, Brynne Campbell; Melkus, Gail D'Eramo; Shenkar, Liat; Mortejo, Marie Claire R; Johnson, Stephen B

Zheng, Yaguang; Dickson, Victoria Vaughan; Blecker, Saul; Ng, Jason M; Rice, Brynne Campbell; Melkus, Gail D'Eramo; Shenkar, Liat; Mortejo, Marie Claire R; Johnson, Stephen B.

Afiliación

Zheng Y; Rory Meyers College of Nursing, New York University, New York, NY, United States.
Dickson VV; Rory Meyers College of Nursing, New York University, New York, NY, United States.
Blecker S; Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States.
Ng JM; Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, United States.
Rice BC; Division of Libraries, New York University, New York, NY, United States.
Melkus GD; Rory Meyers College of Nursing, New York University, New York, NY, United States.
Shenkar L; Lehigh Valley Health Network, Lehigh Valley Reilly Children's Hospital, Allentown, PA, United States.
Mortejo MCR; Rory Meyers College of Nursing, New York University, New York, NY, United States.
Johnson SB; Department of Population Health, Grossman School of Medicine, New York University, New York, NY, United States.

JMIR Diabetes ; 7(2): e34681, 2022 May 16.

Article en En | MEDLINE | ID: mdl-35576579

Palabras clave

diabetes; electronic health records; hypoglycemia; natural language processing

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies / Systematic_reviews Idioma: En Revista: JMIR Diabetes Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Canadá

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