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Medical Decision Making : an International Journal of the Society for Medical Decision Making|January 1, 2014
Sensitivity and specificity can change in opposite directions when new predictive markers are added to risk modelsBen Van Calster, Ewout W Steyerberg, Ralph B D'Agostino, et al.Statistical Methods in Medical Research|May 14, 2020
Regression shrinkage methods for clinical prediction models do not guarantee improved performance: Simulation studyBen Van Calster, Maarten van Smeden, Bavo De Cock, et al.Journal of Clinical Epidemiology|November 28, 2017
Poor performance of clinical prediction models: the harm of commonly applied methodsEwout W Steyerberg, Hajime Uno, John P A Ioannidis, et al.Journal of the American Medical Informatics Association : JAMIA|August 3, 2019
Predictive analytics in health care: how can we know it works?Ben Van Calster, Laure Wynants, Dirk Timmerman, et al.BMC Medicine|December 18, 2019
Calibration: the Achilles heel of predictive analyticsBen Van Calster, David J McLernon, Maarten van Smeden, et al.Statistics in Medicine|February 20, 2014
Assessing calibration of multinomial risk prediction modelsKirsten Van Hoorde, Yvonne Vergouwe, Dirk Timmerman, et al.Statistics in Medicine|June 27, 2012
Extending the c-statistic to nominal polytomous outcomes: the Polytomous Discrimination IndexBen Van Calster, Vanya Van Belle, Yvonne Vergouwe, et al.Journal of Clinical Epidemiology|January 17, 2016
A calibration hierarchy for risk models was defined: from utopia to empirical dataBen Van Calster, Daan Nieboer, Yvonne Vergouwe, et al.Journal of Clinical Epidemiology|February 15, 2019
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction modelsEvangelia Christodoulou, Jie Ma, Gary S Collins, et al.BMC Medicine|October 26, 2019
Three myths about risk thresholds for prediction modelsLaure Wynants, Maarten van Smeden, David J McLernon, et al.Pageof 109