{ "item_title" : "Medical Risk Prediction Models", "item_author" : [" Thomas A. Gerds", "Michael W. Kattan "], "item_description" : "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.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/0/36/767/373/0367673738_b.jpg", "price_data" : { "retail_price" : "72.99", "online_price" : "72.99", "our_price" : "72.99", "club_price" : "72.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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