Comparacion de estrategias de control predictivo estocástico no lineal aplicadas a la quimioterapia

El modelado matemático de sistemas biomédicos puede ayudar a los profesionales oncológicos a diseñar ciclos de administración de fármacos más seguros y eficaces. Para lograr este objetivo, en el proceso de toma de decisiones se utiliza el modelo matemático del crecimiento tumoral y el impacto de la quimioterapia. Sin embargo, los sistemas biomédicos son propensos a un alto grado de incertidumbre, no solo por los errores de medición, sino también por la dinámica del sistema no modelada y la variabilidad entre pacientes. Para abordar este problema, se han aplicado restricciones probabilísticas al control del proceso de administración de fármacos, haciéndolo más robusto frente a perturbaciones. Este trabajo compara una versión no lineal y otra linealizada de las formulaciones estocásticas del control predictivo basado en modelo. Ambos algoritmos mejoran la eficacia y la seguridad del tratamiento, con diferencias en cuanto a conservadurismo y coste computacional.

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Comparacion de estrategias de control predictivo estocástico no lineal aplicadas a la quimioterapia

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