MS035A Computational Models and Methods for Predicting Cancer Progression and Treatment Response I
MS Corresponding Organizer: Dr. Guillermo Lorenzo (University of A Coruña)
Chaired by:
Dr. Guillermo Lorenzo (University of A Coruña , Spain)
Dr. Guillermo Lorenzo (University of A Coruña , Spain)
Scheduled presentations:
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Bayesian information-theoretic approach to determine effective scanning protocols of cancer patients
H. Cho*, A. Lewis, K. Storey -
Integrating Mass Effects in Glioma Radiotherapy Planning by Optimization of a Data and Physics Informed Discrete Loss
M. Balcerak*, B. Menze -
A data-driven physics-based model for predicting prostate cancer progression from the PSA blood test
D. Camacho-Gomez*, C. Borau, J. Garcia-Aznar, M. Gomez-Benito, M. Perez -
Personalized Imaging-Informed Forecasting of Prostate Cancer Progression during Active Surveillance
G. Lorenzo*, C. Wu, J. P. Yung, J. F. Ward, H. Gomez, A. Reali, T. E. Yankeelov, A. M. Venkatesan, T. J. R. Hughes -
A multidisciplinary approach to the therapeutic resistance of prostate cancer
M. Cerasuolo*, A. Burbanks, R. Ronca, A. Ligresti -
Agent-based and continuum models for spatial dynamics of infection by oncolytic viruses
D. Morselli, M. Delitala*, F. Frascoli