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[01958] How can we make tumour predictions under mechanism uncertainty?

  • Session Time & Room : 5D (Aug.25, 15:30-17:10) @D515
  • Type : Contributed Talk
  • Abstract : The need of quantitative tumour growth and progression predictions is pivotal for designing individualized therapies. Medical data correspond to snapshots in time of the patient’s state and their collection relies on patient’s clinical presentation. Current standard of care faces the following challenges: (C1) data collection is sparse in time and (C2) we lack the knowledge of the underlying biological mechanisms. To solve them, I will present a methodology that combines mechanistic modelling and machine.
  • Classification : 92-08
  • Format : Talk at Waseda University
  • Author(s) :
    • Haralampos Hatzikirou (Khalifa University)