Optimized Response-Adaptive Clinical Trials: Sequential Treatment Allocation Based on Markov Decision Problems: BestMasters
Autor Thomas Ondraen Limba Engleză Paperback – 18 dec 2014
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Specificații
ISBN-13: 9783658083434
ISBN-10: 3658083433
Pagini: 120
Ilustrații: XV, 102 p. 14 illus.
Dimensiuni: 148 x 210 x 10 mm
Greutate: 0.17 kg
Ediția:2015
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Seria BestMasters
Locul publicării:Wiesbaden, Germany
ISBN-10: 3658083433
Pagini: 120
Ilustrații: XV, 102 p. 14 illus.
Dimensiuni: 148 x 210 x 10 mm
Greutate: 0.17 kg
Ediția:2015
Editura: Springer Fachmedien Wiesbaden
Colecția Springer Spektrum
Seria BestMasters
Locul publicării:Wiesbaden, Germany
Public țintă
ResearchCuprins
Introduction to Markov Decision Problems and Examples.- Finite and Infinite Horizon Markov Decision Problems.- Solution Algorithms: Backward Induction, Value Iteration and Policy Iteration.- Designing Response Adaptive Clinical Trials with Markov Decision Problems.
Recenzii
“It is a remarkably concise exposition of the use ofMDPs in a pharmaceutical setting; as such, the book’s audience is theintersection of researchers and students with a sophisticated mathematicalbackground and professionals in the pharmaceutical industry. … the book is avery sophisticated treatise on MDP models for managing response-adaptiveclinical trials and both mathematicians and pharmaceutical professionals wouldappreciate it.” (James Smith, Interfaces, Vol. 45 (4), July–August, 2015)
Notă biografică
Thomas Ondra obtained his Master of Science degree in mathematics at University of Vienna. He is a research assistant and PhD student at the Section for Medical Statistics of Medical University of Vienna.
Textul de pe ultima copertă
Two-armed response-adaptive clinical trials are modelled as Markov decision problems to pursue two overriding objectives: Firstly, to identify the superior treatment at the end of the trial and, secondly, to keep the number of patients receiving the inferior treatment small. Such clinical trial designs are very important, especially for rare diseases. Thomas Ondra presents the main solution techniques for Markov decision problems and provides a detailed description how to obtain optimal allocation sequences.
Contents
Thomas Ondra obtained his Master of Science degree in mathematics at University of Vienna. He is a research assistant and PhD student at the Section for Medical Statistics of Medical University of Vienna.
Contents
- Introduction to Markov Decision Problems and Examples
- Finite and Infinite Horizon Markov Decision Problems
- Solution Algorithms: Backward Induction, Value Iteration and Policy Iteration
- Designing Response Adaptive Clinical Trials with Markov Decision Problems
- Researchers and students in the fields of mathematics and statistics
- Professionals in the pharmaceutical industry<
Thomas Ondra obtained his Master of Science degree in mathematics at University of Vienna. He is a research assistant and PhD student at the Section for Medical Statistics of Medical University of Vienna.
Caracteristici
Publication in the field of natural sciences Includes supplementary material: sn.pub/extras