Medical Risk Prediction Models: With Ties to Machine Learning

Gerds, Thomas A., Kattan, Michael W.

Medical Risk Prediction Models: With Ties to Machine Learning

商品描述

Medical Risk Prediction Models: With Ties to Machine Learning is a hands-on book for clinicians, epidemiologists, and professional statisticians who need to make or evaluate a statistical prediction model based on data. The subject of the book is the patient's individualized probability of a medical event within a given time horizon. Gerds and Kattan describe the mathematical details of making and evaluating a statistical prediction model in a highly pedagogical manner while avoiding mathematical notation. Read this book when you are in doubt about whether a Cox regression model predicts better than a random survival forest.

Features:

 

 

 

 

 

  • All you need to know to correctly make an online risk calculator from scratch
  • Discrimination, calibration, and predictive performance with censored data and competing risks
  • R-code and illustrative examples
  • Interpretation of prediction performance via benchmarks
  • Comparison and combination of rival modeling strategies via cross-validation

Thomas A. Gerds is a professor at the Biostatistics Unit at the University of Copenhagen and is affiliated with the Danish Heart Foundation. He is the author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years.

Michael W. Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision-Making Research.

商品描述(中文翻譯)

《醫療風險預測模型：與機器學習的聯繫》是一本針對臨床醫生、流行病學家和專業統計學家的實用書籍，這些人需要根據數據來建立或評估統計預測模型。本書的主題是患者在特定時間範圍內發生醫療事件的個體化概率。Gerds 和 Kattan 以高度教學性的方式描述了建立和評估統計預測模型的數學細節，同時避免使用數學符號。當你對 Cox 回歸模型是否比隨機生存森林預測得更好感到疑惑時，請閱讀本書。

特色：

- 所有你需要知道的，從零開始正確製作在線風險計算器
- 在有審查數據和競爭風險的情況下的區分、校準和預測性能
- R 代碼和示例
- 通過基準解釋預測性能
- 通過交叉驗證比較和結合競爭建模策略

Thomas A. Gerds 是哥本哈根大學生物統計單位的教授，並與丹麥心臟基金會有關聯。他是多個 R 套件的作者，並且多年來為非統計學家教授統計課程。

Michael W. Kattan 是一位被高度引用的作者，並擔任克里夫蘭診所定量健康科學系的主任。他是美國統計協會的會士，並曾獲得醫療決策協會的兩項獎項：尤金·L·桑格卓越服務獎和約翰·M·艾森伯格醫療決策研究實用應用獎。

作者簡介

Thomas A. Gerds is professor at the biostatistics unit at the University of Copenhagen. He is affiliated with the Danish Heart Foundation. He is author of several R-packages on CRAN and has taught statistics courses to non-statisticians for many years.

Michael Kattan is a highly cited author and Chair of the Department of Quantitative Health Sciences at Cleveland Clinic. He is a Fellow of the American Statistical Association and has received two awards from the Society for Medical Decision Making: the Eugene L. Saenger Award for Distinguished Service, and the John M. Eisenberg Award for Practical Application of Medical Decision Making Research.

作者簡介(中文翻譯)

Thomas A. Gerds 是哥本哈根大學生物統計單位的教授。他與丹麥心臟基金會有關聯。他是多個在 CRAN 上的 R 套件的作者，並且多年來一直教授非統計學家的統計課程。

Michael Kattan 是一位被高度引用的作者，並且是克里夫蘭診所定量健康科學系的主任。他是美國統計協會的會士，並且曾獲得醫學決策協會的兩項獎項：尤金·L·桑傑獎以表彰其卓越服務，以及約翰·M·艾森伯格獎以表彰醫學決策研究的實際應用。

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