Statistical methods for dynamic treatment regimes : reinforcement learning, causal inference, and personalized medicine
Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine. This volume demonstrates these methods with their conceptual underpinnings and...
Guardat en:
| Autors principals: | , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
2013.
Cham : Springer Nature |
| Col·lecció: | Statistics for Biology and Health
76 |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Statistical methods for dynamic treatment regimes, reinforcement learning, causal inference, and personalized medicine, Bibhas Chakraborty, Erica E.M. Moodie, 2013, New York, Springer, 1 vol. (XVI-204 p.), Statistics for Biology and Health, 978-1-461-47427-2 • Statistical Methods for Dynamic Treatment Regimes, Texte imprimé, 9781461474296 • Statistical methods for dynamic treatment regimes, reinforcement learning, causal inference, and personalized medicine, Bibhas Chakraborty, Erica E.M. Moodie, 2013, New York, Springer, 1 vol. (XVI-204 p.), Statistics for Biology and Health, 978-1-461-47427-2 |