planning trials and analyzing data for personalized medicine /
نام نخستين پديدآور
edited by Michael Kosorok, Erica Moodie.
وضعیت نشر و پخش و غیره
محل نشرو پخش و غیره
Philadelphia, Pennsylvania :
نام ناشر، پخش کننده و غيره
Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104),
تاریخ نشرو بخش و غیره
[2015]
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (xvi, 348 pages).
فروست
عنوان فروست
ASA-SIAM statistics and applied probability series
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references and index.
یادداشتهای مربوط به مندرجات
متن يادداشت
Preface -- 1. Introduction -- part I. Design of trials for estimating dynamic treatment regimes -- 2. DTRs and SMARTs : definitions, designs, and applications -- 3. Efficient design for clinically relevant intent-to-treat comparisons -- 4. SMART design, conduct, and analysis in oncology -- 5. Sample size calculations for clustered SMART designs -- part II. Practical challenges in dynamic treatment regime analyses -- 6. Analysis in the single-stage setting : an overview of estimation approaches for dynamic treatment regimes -- 7. G-estimation for dynamic treatment regimes in the longitudinal setting -- 8. Outcome weighted learning methods for optimal dynamic treatment regimes -- 9. Value search estimators for optimal dynamic treatment regimes -- 10. Evaluation of longitudinal dynamics with and without marginal structural working models -- 11. Imputation strategy for SMARTs -- 12. Clinical trials for personalized dose finding -- 13. Methods for analyzing DTRs with censored survival data -- 14. Outcome weighted learning with a reject option -- 15. Estimation of dynamic treatment regimes for complex outcomes : balancing benefits and risks -- 16. Practical reinforcement learning in dynamic treatment regimes -- 17. Reinforcement learning applications in clinical trials.
بدون عنوان
0
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient information to optimize that patient's health care, particularly in managing chronic conditions and treating cancer. In the statistical literature, sequential decision making is known as an adaptive treatment strategy (ATS) or a dynamic treatment regime (DTR). The field of DTRs emerges at the interface of statistics, machine learning, and biomedical science to provide a data-driven framework for precision medicine. The authors provide a learning-by-seeing approach to the development of ATSs, aimed at a broad audience of health researchers. All estimation procedures used are described in sufficient heuristic and technical detail so that less quantitative readers can understand the broad principles underlying the approaches. At the same time, more quantitative readers can implement these practices. Adaptive Treatment Strategies in Practice: Planning Trials and Analyzing Data for Personalized Medicine provides the most up-to-date summary of the current state of the statistical research in personalized medicine, contains chapters by leaders in the area from both the statistics and computer sciences fields, contains a range of practical advice, introductory and expository materials, and case studies.
ویراست دیگر از اثر در قالب دیگر رسانه
شماره استاندارد بين المللي کتاب و موسيقي
9781611974171
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Clinical trials-- Statistical methods.
موضوع مستند نشده
Medical statistics.
موضوع مستند نشده
Medicine-- Research-- Statistical methods.
موضوع مستند نشده
Clinical trials-- Statistical methods.
موضوع مستند نشده
Medical statistics.
موضوع مستند نشده
Medicine-- Research-- Statistical methods.
رده بندی ديویی
شماره
610
.
2/1
ويراست
23
رده بندی کنگره
شماره رده
RA409
نشانه اثر
.
A33
2015eb
نام شخص - (مسئولیت معنوی برابر )
مستند نام اشخاص تاييد نشده
Kosorok, Michael R.
مستند نام اشخاص تاييد نشده
Moodie, Erica E. M.
نام تنالگان _ (مسئولیت معنوی برابر)
مستند نام تنالگان تاييد نشده
Society for Industrial and Applied Mathematics,publisher.