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Modelo de predicción basado en aprendizaje automático para mal pronóstico en sepsis utilizando el recuento de
Siang Huang1, Luyao Liu1, Chaoyang Wang1
1Department of Critical Care Medicine, The First Hospital of China Medical University, China Medical University, 155 Nanjing North Street, Heping District, Shenyang City, 110001, Liaoning Province, China.
La identificación de linfopenia persistente en pacientes con sepsis mediante recuentos dinámicos de linfocitos puede predecir malos resultados. Este enfoque ayuda a identificar a personas de alto riesgo para inmunoterapia dirigida, mejorando el manejo de la sepsis.
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