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nexusstc/Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine/e36e54dbe4f71f6febed5d1aa11742db.pdf

Statistical Methods for Dynamic Treatment Regimes: Reinforcement Learning, Causal Inference, and Personalized Medicine (Statistics for Biology and Health Book 76) Bibhas Chakraborty, Erica E.M. Moodie (auth.) Springer-Verlag New York, Statistics for Biology and Health, Statistics for Biology and Health, 1, 2013

**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 with the goal of orienting researchers to the field. The first chapter establishes context for the statistical reader in the landscape of personalized medicine. Readers need only have familiarity with elementary calculus, linear algebra, and basic large-sample theory to use this text. Throughout the text, authors direct readers to available code or packages in different statistical languages to facilitate implementation. In cases where code does not already exist, the authors provide analytic approaches in sufficient detail that any researcher with knowledge of statistical programming could implement the methods from scratch. This will be an important volume for a wide range of researchers, including statisticians, epidemiologists, medical researchers, and machine learning researchers interested in medical applications. Advanced graduate students in statistics and biostatistics will also find material in Statistical Methods for Dynamic Treatment Regimes to be a critical part of their studies.

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英语 [en] · PDF · 2.6MB · 2013 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/scihub/zlib · Save

base score: 11065.0, final score: 17466.738

48 部分匹配

upload/duxiu_main/v/zip/extracted__./jdk-6u30-apidocs.zip/docs/api/java/util/zip/class-use/CRC32.html

Uses of Class java.util.zip.CRC32 (Java Platform SE 6)

HTML · 0.1MB · 📗 未知类型的图书 · 🚀/upload · Save

base score: 9924.0, final score: 4.042965

upload/misc/Y9EgLx762wKqWqG7nloH/Books/Hacking Papers/2023-02-02 - Malware analysis part 7 Yara rule example for CRC32 CRC32 in REvil ransomware.pdf

2023-02-02 - Malware analysis part 7 Yara rule example for CRC32 CRC32 in REvil ransomware.pdf Chromium

PDF · 2.1MB · 📗 未知类型的图书 · 🚀/upload · Save

base score: 10941.0, final score: 3.9241977

lgrsnf/200630.pdf

200630

西班牙语 [es] · PDF · 22.7MB · 📘 非小说类图书 · lgrs · Save

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base score: 0.01, final score: 3.7707977

lgrsnf/201031.pdf

201031

西班牙语 [es] · PDF · 0.7MB · 📘 非小说类图书 · lgrs · Save

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base score: 0.01, final score: 3.7707977

lgrsnf/200535.pdf

200535

西班牙语 [es] · PDF · 0.1MB · 📘 非小说类图书 · lgrs · Save

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base score: 0.01, final score: 3.7707977

lgrsnf/200542.pdf

200542

西班牙语 [es] · PDF · 0.1MB · 📘 非小说类图书 · lgrs · Save

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base score: 0.01, final score: 3.7707977

lgrsnf/201366.pdf

201366

西班牙语 [es] · PDF · 14.8MB · 📘 非小说类图书 · lgrs · Save

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base score: 0.01, final score: 3.7707977

lgrsnf/201413.pdf

201413

西班牙语 [es] · PDF · 21.4MB · 📘 非小说类图书 · lgrs · Save

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