Demographic Prediction Based on User Reviews about Medications



Título del documento: Demographic Prediction Based on User Reviews about Medications
Revista: Computación y Sistemas
Base de datos: PERIÓDICA
Número de sistema: 000423239
ISSN: 1405-5546
Autores: 1
2
Instituciones: 1Kazan Federal University, Kazan. Rusia
2National Research University Higher School of Economics, Laboratory for Internet Studies, San Petersburgo. Rusia
3Steklov Institute of Mathematics, San Petersburgo. Rusia
Año:
Periodo: Abr-Jun
Volumen: 21
Número: 2
País: México
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Analítico, descriptivo
Resumen en inglés Drug reactions can be extracted from user reviews provided on the Web, and processing this information in an automated way represents a novel and exciting approach to personalized medicine and wide-scale drug tests. In medical applications, demographic information regarding the authors of these reviews such as age and gender is of primary importance; however, existing studies usually assume that this information is available or overlook the issue entirely. In this work, we propose and compare several approaches to automated mining of demographic information from user-generated texts. We compare modern natural language processing techniques, including feature rich classifiers, extensions of topic models, and deep neural networks (both convolutional and recurrent architectures) for this problem
Disciplinas: Medicina,
Literatura y lingüística,
Ciencias de la computación
Palabras clave: Salud pública,
Medicación,
Procesamiento de lenguaje natural,
Revisiones de usuarios,
Análisis de textos
Keyword: Public health,
Medication,
Natural language processing,
User reviews
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