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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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
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Nature Portfolio
2021
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| Accès en ligne: | https://doaj.org/article/346e4b6869474fd3982e56778d98ce5a |
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