×


 x 

Shopping cart
Bibhas Chakraborty - Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine - 9781461474272 - V9781461474272
Stock image for illustration purposes only - book cover, edition or condition may vary.

Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine

€ 133.88
FREE Delivery in Ireland
Description for Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine Hardback. Series: Statistics for Biology and Health. Num Pages: 220 pages, 10 black & white tables, biography. BIC Classification: MBNS; PBT. Category: (P) Professional & Vocational. Dimension: 159 x 239 x 22. Weight in Grams: 470.
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 illustration through analysis of real and simulated data. These methods are immediately applicable to the practice of personalized medicine, which is a medical paradigm that emphasizes the systematic use of individual patient information to optimize patient health care. This is the first single source to provide an overview of methodology and results gathered from journals, proceedings, and technical reports ... Read more

Product Details

Publisher
Springer-Verlag New York Inc. United States
Number of pages
219
Format
Hardback
Publication date
2013
Series
Statistics for Biology and Health
Condition
New
Weight
470g
Number of Pages
204
Place of Publication
New York, NY, United States
ISBN
9781461474272
SKU
V9781461474272
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15

About Bibhas Chakraborty
Bibhas Chakraborty is an Assistant Professor of Biostatistics at the Mailman School of Public Health, Columbia University. His primary research interests lie in dynamic treatment regimes, machine learning and data mining including reinforcement learning, causal inference, and design and analysis of clinical trials. He received a Bachelor's degree from the University of Calcutta, a Master's degree from the Indian Statistical ... Read more

Reviews for Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine
From the reviews: Overall, the book provides an excellent reviewof DTRs up to date. After finishing reading the book, I planned to create a post-graduate seminar course on this topic using this book as a textbook. I enthusiastically recommend this book. This book will be a valuable reference for anyone interested and involved in research on ... Read more

Goodreads reviews for Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine


Subscribe to our newsletter

News on special offers, signed editions & more!