Reinforcement learning derived chemotherapeutic schedules for robust patient-specific therapy
Abstract The in-silico development of a chemotherapeutic dosing schedule for treating cancer relies upon a parameterization of a particular tumour growth model to describe the dynamics of the cancer in response to the dose of the drug. In practice, it is often prohibitively difficult to ensure the v...
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Autores principales: | Brydon Eastman, Michelle Przedborski, Mohammad Kohandel |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/346e4b6869474fd3982e56778d98ce5a |
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