Related references
Note: Only part of the references are listed.Probability estimation with machine learning methods for dichotomous and multicategory outcome: Theory
Jochen Kruppa et al.
BIOMETRICAL JOURNAL (2014)
Probability estimation with machine learning methods for dichotomous and multicategory outcome: Applications
Jochen Kruppa et al.
BIOMETRICAL JOURNAL (2014)
Using methods from the data-mining and machine-learning literature for disease classification and prediction: a case study examining classification of heart failure subtypes
Peter C. Austin et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2013)
Predictive accuracy of risk factors and markers: a simulation study of the effect of novel markers on different performance measures for logistic regression models
Peter C. Austin et al.
STATISTICS IN MEDICINE (2013)
Prognosis Research Strategy (PROGRESS) 3: Prognostic Model Research
Ewout W. Steyerberg et al.
PLOS MEDICINE (2013)
Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?
Peter C. Austin et al.
BIOMETRICAL JOURNAL (2012)
Prediction of outcome after moderate and severe traumatic brain injury: External validation of the International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models
Bob Roozenbeek et al.
CRITICAL CARE MEDICINE (2012)
A Mathematical Model for Interpretable Clinical Decision Support with Applications in Gynecology
Vanya M. C. A. Van Belle et al.
PLOS ONE (2012)
Extending the c-statistic to nominal polytomous outcomes: the Polytomous Discrimination Index
Ben Van Calster et al.
STATISTICS IN MEDICINE (2012)
Prediction of intracranial findings on CT-scans by alternative modelling techniques
Tjeerd van der Ploeg et al.
BMC MEDICAL RESEARCH METHODOLOGY (2011)
The PREMM1,2,6 Model Predicts Risk of MLH1, MSH2, and MSH6 Germline Mutations Based on Cancer History
Fay Kastrinos et al.
GASTROENTEROLOGY (2011)
Polytomous diagnosis of ovarian tumors as benign, borderline, primary invasive or metastatic: development and validation of standard and kernel-based risk prediction models
Ben Van Calster et al.
BMC MEDICAL RESEARCH METHODOLOGY (2010)
An application of methods for the probabilistic three-class classification of pregnancies of unknown location
Ben Van Calster et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2009)
A systematic review finds methodological improvements necessary for prognostic models in determining traumatic brain injury outcomes
Nino A. Mushkudiani et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2008)
Predicting outcome after traumatic brain injury: practical prognostic models based on large cohort of international patients
Pablo Perel et al.
BMJ-BRITISH MEDICAL JOURNAL (2008)
Predicting outcome after traumatic brain injury: Development and international validation of prognostic scores based on admission characteristics
Ewout W. Steyerberg et al.
PLOS MEDICINE (2008)
Automated variable selection methods for logistic regression produced unstable models for predicting acute myocardial infarction mortality
PC Austin et al.
JOURNAL OF CLINICAL EPIDEMIOLOGY (2004)
Statistical modeling: The two cultures
L Breiman
STATISTICAL SCIENCE (2001)