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De los grandes datos a las decisiones impulsadas por la IA en la apnea obstructiva del sueño: una revisión narrativa

Mengying Wu^1,2, Kexin Wang², Huai Huang²

¹School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, People's Republic of China.

Nature and science of sleep

|August 27, 2025

Resumen

La inteligencia artificial (IA) en la investigación de la apnea obstructiva del sueño (AOS) está subutilizada, centrándose en las señales del sueño pero descuidando otros datos. Los análisis de tratamiento personalizado (prescriptivos) son escasos, lo que dificulta la toma de decisiones clínicas.

Área de la Ciencia:

Medicina del sueño
Inteligencia artificial
Ciencia de los datos

Sus antecedentes:

La apnea obstructiva del sueño (AOS) es una condición prevalente a menudo subdiagnosticada y subtratada.
Los avances en inteligencia artificial (IA) ofrecen soluciones potenciales para la gestión de OSA.
Los recursos de datos multimodales para OSA se están expandiendo rápidamente.

Objetivo del estudio:

Revisar exhaustivamente la utilización de las técnicas de IA en los recursos de datos de la apnea obstructiva del sueño (AOS).
Analizar la aplicación de la IA en diferentes tipos de datos y fases analíticas (descriptivo, diagnóstico, predictivo y prescriptivo).
Identificar las lagunas en las aplicaciones actuales de IA para OSA y proporcionar recomendaciones para futuras investigaciones.

Principales métodos:

Se realizó una búsqueda sistemática de la literatura en las principales bases de datos científicas (PubMed, Web of Science, Scopus, IEEE Xplore) desde abril de 2020 hasta abril de 2025.
Los términos de búsqueda combinaron palabras clave relacionadas con la IA con "apnea obstructiva del sueño".
El modelo de análisis DDPP (Descriptivo, Diagnóstico, Predictivo, Prescriptivo) se utilizó para categorizar las aplicaciones de IA.

Principales resultados:

De 575 estudios, la mayoría de las investigaciones de IA se centraron en señales de monitoreo del sueño.
Los resultados informados por los pacientes, los registros electrónicos de salud y los datos ambientales siguen sin utilizarse.
Las aplicaciones clínicas actuales se centran predominantemente en la IA descriptiva y diagnóstica, con análisis prescriptivos limitados para la terapia personalizada.

Conclusiones:

Hay una brecha significativa entre los datos disponibles de OSA y las aplicaciones actuales de IA.
La investigación futura debe aprovechar las diversas dimensiones de los datos OSA y seleccionar las tecnologías de IA adecuadas.
La utilización mejorada de la IA puede mejorar la toma de decisiones clínicas y el tratamiento personalizado para la AOS.

Palabras clave:

Inteligencia artificial grandes cantidades de datos marco para el análisis de datos Apnea obstructiva del sueño

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