Portal de Periódicos da CAPES

Clinical Prediction Models

2008; Springer Nature; Linguagem: Inglês

10.1007/978-0-387-77244-8

1431-8776

Ewout W. Steyerberg,

Machine Learning in Healthcare

Prediction models are important in various fields, including medicine, physics, meteorology, and finance.Prediction models will become more relevant in the medical field with the increase in knowledge on potential predictors of outcome, e.g. from genetics.Also, the number of applications will increase, e.g. with targeted early detection of disease, and individualized approaches to diagnostic testing and treatment.The current era of evidence-based medicine asks for an individualized approach to medical decision-making.Evidence-based medicine has a central place for meta-analysis to summarize results from randomized controlled trials; similarly prediction models may summarize the effects of predictors to provide individualized predictions of a diagnostic or prognostic outcome. Intended AudienceReaders should have a basic knowledge of biostatistics, especially regression analysis, but no strong background in mathematics is required.The number of formulas is deliberately kept small.Usually a bottom-up approach is followed in teaching regression analysis techniques, starting with model assumptions, estimation methods, and basic interpretation.This book is more top-down: given that we want to predict an outcome, how can we best utilize regression techniques?