Support Vector Machines and logistic regression to predict temporal artery biopsy outcomes.

[1]  Jayashree Kalpathy-Cramer,et al.  Machine Learning Has Arrived! , 2017, Ophthalmology.

[2]  John J. Chen,et al.  Multivariable prediction model for suspected giant cell arteritis: development and validation , 2017, Clinical ophthalmology.

[3]  Heejung Bang,et al.  How to Establish Clinical Prediction Models , 2016, Endocrinology and metabolism.

[4]  G. Collins,et al.  Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement , 2015, Annals of Internal Medicine.

[5]  A. Hewitt,et al.  Projected Worldwide Disease Burden from Giant Cell Arteritis by 2050 , 2015, The Journal of Rheumatology.

[6]  Gordon D. Murray,et al.  Comparison of Statistical and Clinical Predictions of Functional Outcome after Ischemic Stroke , 2014, PloS one.

[7]  G. Rebolleda,et al.  A calculator for temporal artery biopsy result prediction in giant cell arteritis suspects. , 2014, European journal of internal medicine.

[8]  M. Sarossy,et al.  The use of statistical modeling to predict temporal artery biopsy outcome from presenting symptoms and laboratory results , 2014 .

[9]  Daniela M. Witten,et al.  An Introduction to Statistical Learning: with Applications in R , 2013 .

[10]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[11]  Filip De Turck,et al.  Bmc Medical Informatics and Decision Making Support Vector Machine versus Logistic Regression Modeling for Prediction of Hospital Mortality in Critically Ill Patients with Haematological Malignancies , 2008 .

[12]  J A K Suykens,et al.  Support vector machines versus logistic regression: improving prospective performance in clinical decision‐making , 2006, Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology.

[13]  R. Dawes,et al.  Heuristics and Biases: Clinical versus Actuarial Judgment , 2002 .

[14]  E. DeLong,et al.  Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. , 1988, Biometrics.