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Uso de aprendizaje automático para predecir cambios en el consumo de alcohol antes del tratamiento

Matison W McCool¹, Frank J Schwebel¹, Robert C Schlauch²

¹Center on Alcohol, Substance Use, and Addiction, The University of New Mexico, Albuquerque, New Mexico, USA.

Alcohol, clinical & experimental research

|February 9, 2026

Resumen

Muchas personas alteran sus hábitos de consumo de alcohol antes del tratamiento formal. Los modelos de aprendizaje automático, en particular las redes neuronales, muestran ser prometedores en la predicción de estos cambios previos al tratamiento, siendo los factores demográficos y psicológicos los predictores clave.

Conclusiones:

Las variables demográficas son predictores significativos de los cambios en el consumo de alcohol antes del tratamiento.
Comprender los factores sociales y demográficos es crucial para abordar los comportamientos de consumo de alcohol antes del tratamiento.
El aprendizaje automático ofrece una vía prometedora para analizar patrones complejos en la investigación sobre adicciones.

Palabras clave:

consumo de alcohol aprendizaje automático cambio previo al tratamiento

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