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Medical Risk Prediction Models: With Ties to Machine Learning
Hardcover
Series: Chapman & Hall/CRC Biostatistics
Medical ReferenceProbability & Statistics
ISBN13: 9781138384477
Publisher: CRC Press
Published: Feb 1 2021
Pages: 312
Weight: 1.36
Height: 0.75 Width: 6.14 Depth: 9.21
Language: English
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.
1 different editions
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Medical Risk Prediction Models: With Ties to Machine Learning
Gerds, Thomas A.
Kattan, Michael W.
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