Medical Risk Prediction Models : With Ties to Machine Learning EPUB
by Thomas A. Gerds, Michael W. Kattan
Part of the Chapman & Hall/CRC Biostatistics Series series
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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-validationThomas 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.
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- Format:EPUB
- Pages:312 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:31/01/2021
- Category:
- ISBN:9780429764233
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Information
-
Download Now
- Format:EPUB
- Pages:312 pages
- Publisher:Taylor & Francis Ltd
- Publication Date:31/01/2021
- Category:
- ISBN:9780429764233