review Open AccessTop 1% cited

A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models

Journal of Clinical Epidemiology · 2019 · Vol. 110 · pp. 12–22

Evangelia Christodoulou(KU Leuven)Jie Ma(Nuffield Orthopaedic Centre)Gary S. Collins(Nuffield Orthopaedic Centre)Ewout W. Steyerberg(Leiden University)Jan Y. Verbakel(University of Oxford)Ben Van Calster✉(Leiden University)

View via DOI Publisher page

Machine Learning in Healthcare Artificial Intelligence in Healthcare Artificial Intelligence in Healthcare and EducationLogistic regressionMachine learningRegressionStatisticsArtificial intelligenceComputer scienceRegression analysisLogistic model treeMedicineMathematics

MeSH terms

Supervised Machine LearningAlgorithmsHumansModels, TheoreticalPredictive Value of TestsSensitivity and SpecificityLogistic ModelsOutcome Assessment, Health CareArea Under Curve

Funding

Cancer Research UK
Fonds Wetenschappelijk Onderzoek
KU Leuven

Citations

1,841

FWCI

121.41

field-weighted impact

References

125

Percentile

100%

vs. same field & year

Citations per year

Cited by

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References

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PLoS Medicine · 2014 · 1,871 citations

Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement

Annals of Internal Medicine · 2015 · 2,750 citations

QUADAS-2: A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies

Annals of Internal Medicine · 2011 · 13,616 citations

Machine Learning in Medicine

Circulation · 2015 · 3,320 citations

Guidelines for Developing and Reporting Machine Learning Predictive Models in Biomedical Research: A Multidisciplinary View

Journal of Medical Internet Research · 2016 · 1,002 citations

Random forest versus logistic regression: a large-scale benchmark experiment

BMC Bioinformatics · 2018 · 824 citations

Reporting and Interpreting Decision Curve Analysis: A Guide for Investigators

European Urology · 2018 · 1,241 citations

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