Clinical prediction models estimate the risk of existing disease or future outcome for an individual, which is conditional on the values of multiple predictors such as age, sex, and biomarkers. In this article, Bonnett and colleagues provide a guide to presenting clinical prediction models so that they can be implemented in practice, if appropriate. They describe how to create four presentation formats and discuss the advantages and disadvantages of each format. A key message is the need for stakeholder engagement to determine the best presentation option in relation to the clinical context of use and the intended user
Prediction models are developed to aid health care providers in estimating the probability or risk t...
Background: Prediction models are developed to aid healthcare providers in estimating the probabilit...
BackgroundPrediction models are developed to aid healthcare providers in estimating the probability ...
For permission to use (where not already granted under a licence) please go to. Clinical prediction ...
Clinical prediction models play an increasingly important role in contemporary clinical care, by inf...
Clinical prediction models provide risk estimates for the presence of disease (diagnosis) or an even...
IMPORTANCE Prognostication is an important aspect of clinical decision-making, but it is often chall...
textabstractClinical prediction models provide risk estimates for the presence of disease (diagnosis...
A clinical prediction model can be applied to several challenging clinical scenarios: screening high...
Prediction models aim to use available data to predict a health state or outcome that has not yet be...
BACKGROUND: Prediction models are developed to aid healthcare providers in estimating the probabilit...
Background: Prediction models, both diagnostic and prognostic, are developed with the aim to guide c...
Prediction models aim to use available data to predict a health state or outcome that has not yet be...
Context: Prediction models are developed to aid health care providers in estimating the probability ...
BACKGROUND: Prediction models are developed to aid health care providers in estimating the probabili...
Prediction models are developed to aid health care providers in estimating the probability or risk t...
Background: Prediction models are developed to aid healthcare providers in estimating the probabilit...
BackgroundPrediction models are developed to aid healthcare providers in estimating the probability ...
For permission to use (where not already granted under a licence) please go to. Clinical prediction ...
Clinical prediction models play an increasingly important role in contemporary clinical care, by inf...
Clinical prediction models provide risk estimates for the presence of disease (diagnosis) or an even...
IMPORTANCE Prognostication is an important aspect of clinical decision-making, but it is often chall...
textabstractClinical prediction models provide risk estimates for the presence of disease (diagnosis...
A clinical prediction model can be applied to several challenging clinical scenarios: screening high...
Prediction models aim to use available data to predict a health state or outcome that has not yet be...
BACKGROUND: Prediction models are developed to aid healthcare providers in estimating the probabilit...
Background: Prediction models, both diagnostic and prognostic, are developed with the aim to guide c...
Prediction models aim to use available data to predict a health state or outcome that has not yet be...
Context: Prediction models are developed to aid health care providers in estimating the probability ...
BACKGROUND: Prediction models are developed to aid health care providers in estimating the probabili...
Prediction models are developed to aid health care providers in estimating the probability or risk t...
Background: Prediction models are developed to aid healthcare providers in estimating the probabilit...
BackgroundPrediction models are developed to aid healthcare providers in estimating the probability ...