Medical Risk Prediction Models With Ties To Machine Learning (Thomas A. Gerds)

[Farid]

English | 2021 | ISBN: 9781138384484 | 313 pages | True PDF | 6.64 MB 0367673738

Catergory: Mathematics, Medical, Nonfiction

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.

Contents of Download:
📌 Medical Risk Prediction Models.pdf (Thomas A. Gerds) (2022) (6.64 MB)

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⭐️ Medical Risk Prediction Models With Ties To Machine Learning ✅ (6.64 MB)
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