Medical Risk Prediction Models

<p><strong>Medical Risk Prediction Models: With Ties to Machine Learning</strong> 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.</p><p><b>Features:</b></p><ul> <ul> <li>All you need to know to correctly make an online risk calculator from scratch.</li> </ul> </ul><ul> <ul> <li>Discrimination calibration and predictive performance with censored data and competing risks.</li> </ul> </ul><ul> <ul> <li>R-code and illustrative examples.</li> </ul> </ul><ul> <ul> <li>Interpretation of prediction performance via benchmarks.</li> </ul> </ul><ul> <ul> <li>Comparison and combination of rival modeling strategies via cross-validation.</li> </ul> </ul>