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Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics

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Medical Risk Prediction Models - With Ties to Machine Learning (Hardcover) Loot Price: R4,216
Discovery Miles 42 160
Medical Risk Prediction Models - With Ties to Machine Learning (Hardcover): Thomas A. Gerds, Michael W. Kattan

Medical Risk Prediction Models - With Ties to Machine Learning (Hardcover)

Thomas A. Gerds, Michael W. Kattan

Series: Chapman & Hall/CRC Biostatistics Series

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Loot Price R4,216 Discovery Miles 42 160 | Repayment Terms: R395 pm x 12*

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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-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.

General

Imprint: Crc Press
Country of origin: United Kingdom
Series: Chapman & Hall/CRC Biostatistics Series
Release date: February 2021
First published: 2022
Authors: Thomas A. Gerds • Michael W. Kattan
Dimensions: 234 x 156 x 27mm (L x W x T)
Format: Hardcover
Pages: 290
ISBN-13: 978-1-138-38447-7
Categories: Books > Science & Mathematics > Mathematics > Probability & statistics
Books > Science & Mathematics > Biology, life sciences > General
Books > Medicine > General issues > Public health & preventive medicine > Epidemiology & medical statistics
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LSN: 1-138-38447-X
Barcode: 9781138384477

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