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Medical Risk Prediction Models
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Medical Risk Prediction Models : With Ties to Machine Learning

Book Details

Format Paperback / Softback
ISBN-10 0367673738
ISBN-13 9780367673734
Publisher Taylor & Francis Ltd
Imprint Chapman & Hall/CRC
Country of Manufacture GB
Country of Publication GB
Publication Date Aug 29th, 2022
Print length 312 Pages
Weight 480 grams
Dimensions 15.60 x 23.30 x 2.00 cms
Ksh 9,900.00
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The backbone of medical decision making is prediction. Statistical prediction models can help in medical decision making. This book takes the viewpoint of the single patient and asks what does it mean that a risk prediction model performs well for a single individual?

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.


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