In silico chemotherapy optimization with genetic algorithm

MF Dömény, M Puskás, L Kovács… - 2023 IEEE 17th …, 2023 - ieeexplore.ieee.org
The combination of medicine with engineering has great potential. The currently used
chemotherapy treatments usually use maximal tolerable doses, which can lead to harmful …

Model predictive fuzzy control in chemotherapy optimization

TD Szűcs, M Puskás, DA Drexler… - 2023 IEEE 17th …, 2023 - ieeexplore.ieee.org
Nowadays clinical therapies in chemotherapy sessions are generalized for patients,
therefore we are working to provide a personalized drug plan to help reduce the drug …

Tumor model parameter estimation for therapy optimization using artificial neural networks

M Puskás, DA Drexler - 2021 IEEE International Conference on …, 2021 - ieeexplore.ieee.org
Therapy optimization and personalization in cancer treatment requires reliable mathematical
models. A key issue in personalization is the identification of the model parameters. We …

Parameter estimation from realistic experiment scenario using artificial neural networks

M Puskás, B Gergics, A Ládi… - 2022 IEEE 16th …, 2022 - ieeexplore.ieee.org
One of the promising directions in future medicine is the optimization of therapies based on
mathematical and engi-neering methods, with which the treatment can be personalized. In …

Time-varying parameter identification of a tumor growth model using moving horizon estimation

B Czakó, DA Drexler, L Kovács - 2022 IEEE 26th International …, 2022 - ieeexplore.ieee.org
A nonlinear Moving Horizon Estimator (MHE) was developed which can estimate the time-
varying parameters of a tumor growth model under chemotherapeutic treatment. We …

Noise modeling of tumor size measurements from animal experiments for virtual patient generation

M Puskás, B Gergics, B Gombos… - 2023 IEEE 27th …, 2023 - ieeexplore.ieee.org
Optimizing computer-generated therapy may be one of the most promising tools for future
medical treatments. In silico experiments are crucial for therapy planning and testing, this …

Population-based chemotherapy optimization using genetic algorithm

MF Dömény, M Puskás, L Kovács… - 2023 IEEE 21st Jubilee …, 2023 - ieeexplore.ieee.org
We can enhance the current medical technology by introducing engineering methods. The
current chemotherapy treatments are designed for the average and are only taking into …

Tracking parameter changes of an impulsive tumor growth model

E Nagy, B Czakó, M Siket, B Gombos… - 2022 IEEE 10th …, 2022 - ieeexplore.ieee.org
Personalization of chemotherapy requires a mathematical model tailored to the patient. The
tailoring requires the knowledge of the parameters specific to the patient, however, these …

The effect of the choice of initial estimation for a tumor model parameter estimation problem

E Nagy, DA Drexler - … Intelligence and Informatics and 8th IEEE …, 2022 - ieeexplore.ieee.org
Cyber-medical systems provides lots of possibilities that help doctors plan more effective
treatments. A reliable mathematical model that can be customized is essential for therapy …

A review on modeling tumor dynamics and agent reward functions in reinforcement learning based therapy optimization

MG Almásy, A Hörömpő, D Kiss… - Journal of Intelligent & …, 2022 - content.iospress.com
Revolutionary changes of deep reinforcement learning are leading to high-performing
intelligent solutions in multiple fields, including healthcare. At the moment, chemotherapy …