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Interacciones Huésped-Microbio: Perspectivas de las Tecnologías de Aprendizaje Automático y Aprendizaje Profundo en

Yiting Lu^1,2,3, Xiaowen Li^1,2,3, A M Abd El-Aty^4,5

¹Marine Medical Research and Development Centre, Shenzhen Institute, Guangdong Ocean University, Shenzhen 518120, China.

Veterinary sciences

|December 31, 2025

Resumen

El aprendizaje automático (ML) y el aprendizaje profundo (DL) ofrecen herramientas poderosas para combatir las enfermedades virales en animales al predecir las interacciones huésped-microbio y acelerar el descubrimiento de fármacos. Los avances futuros apuntan a sistemas adaptativos que integren virología, inmunología y epidemiología para una prevención precisa de enfermedades.

Sus antecedentes:

La producción ganadera industrializada aumenta los riesgos de epidemias virales.
La comprensión de las interacciones virus-huésped es crucial para el control de patógenos.
Las enfermedades virales en animales afectan los sistemas intestinal, respiratorio y reproductivo.

Conclusiones:

El ML y el DL proporcionan herramientas basadas en datos para la ciencia veterinaria.
Los desafíos incluyen limitaciones de datos y aplicabilidad trans-especies de modelos.
El trabajo futuro requiere algoritmos especializados y sistemas inteligentes integrados para la prevención adaptativa de enfermedades.
La combinación de aprendizaje por refuerzo y no supervisado puede optimizar la vacunación y detectar patógenos emergentes.

Palabras clave:

monitoreo del crecimiento animal enfermedades virales en animales aprendizaje profundo interacciones entre huésped y microorganismos aprendizaje automático

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