Cargando…
Reinforcement Learning for Precision Oncology
SIMPLE SUMMARY: The accelerating merger of information technology and cancer research heralds the advent of novel methods and models for clinical decision making in oncology. Reinforcement learning—as one of the major subspecialties in machine learning—holds the potential for the development of high...
Autores principales: | Eckardt, Jan-Niklas, Wendt, Karsten, Bornhäuser, Martin, Middeke, Jan Moritz |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8472712/ https://www.ncbi.nlm.nih.gov/pubmed/34572853 http://dx.doi.org/10.3390/cancers13184624 |
Ejemplares similares
-
Semi-supervised learning in cancer diagnostics
por: Eckardt, Jan-Niklas, et al.
Publicado: (2022) -
Deep learning detects acute myeloid leukemia and predicts NPM1 mutation status from bone marrow smears
por: Eckardt, Jan-Niklas, et al.
Publicado: (2021) -
Deep learning identifies Acute Promyelocytic Leukemia in bone marrow smears
por: Eckardt, Jan-Niklas, et al.
Publicado: (2022) -
Prevention and treatment of tumor lysis syndrome, and the efficacy and role of rasburicase
por: Alakel, Nael, et al.
Publicado: (2017) -
Reinforcement learning and Bayesian data assimilation for model‐informed precision dosing in oncology
por: Maier, Corinna, et al.
Publicado: (2021)