Predicción y control del Trastorno por déficit de Atención con Hiperactividad en adultos: Una revisión de literatura
Prediction and control of attention deficit hyperactivity disorder in adults: a review of the literature
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La investigación aborda la necesidad de mejorar el diagnóstico y tratamiento del Trastorno por Déficit de Atención e Hiperactividad (TDAH) en adultos. Se propone utilizar técnicas de machine learning (ML) para desarrollar herramientas de predicción y diagnóstico temprano, así como estrategias de intervención personalizadas. Se llevó a cabo una exhaustiva Revisión Sistemática de la Literatura (RSL) utilizando bases de datos especializadas como PubMed, Scopus, ScienceDirect y SpringerLink, con criterios de inclusión y exclusión definidos. Los hallazgos revelaron la eficacia de enfoques personalizados, que consideran factores individuales como el estilo de vida y el entorno social, además de los síntomas clínicos. Estos enfoques no solo mejoraron la precisión del diagnóstico, sino que también permitieron diseñar estrategias de tratamiento adaptadas a las necesidades de cada paciente. Esto resalta la importancia de integrar técnicas de ML en la personalización de intervenciones para mejorar la calidad de vida de los adultos con TDAH.
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