TY  - JOUR
AU  - Navarini, Luca
AU  - Caso, Francesco
AU  - Costa, Luisa
AU  - Currado, Damiano
AU  - Stola, Liliana
AU  - Perrotta, Fabio
AU  - Delfino, Lorenzo
AU  - Sperti, Michela
AU  - Deriu, Marco A
AU  - Ruscitti, Piero
AU  - Pavlych, Viktoriya
AU  - Corrado, Addolorata
AU  - Di Benedetto, Giacomo
AU  - Tasso, Marco
AU  - Ciccozzi, Massimo
AU  - Laudisio, Alice
AU  - Lunardi, Claudio
AU  - Cantatore, Francesco Paolo
AU  - Lubrano, Ennio
AU  - Giacomelli, Roberto
AU  - Scarpa, Raffaele
AU  - Afeltra, Antonella
PY  - 2020
DO  - 10.1007/s40744-020-00233-4
SN  - 2198-6576
UR  - http://hdl.handle.net/10668/16266
T2  - Rheumatology and therapy
AB  - The performance of seven cardiovascular (CV) risk algorithms is evaluated in a multicentric cohort of ankylosing spondylitis (AS) patients. Performance and calibration of traditional CV predictors have been compared with the novel paradigm of machine...
LA  - en
PB  - Springer
KW  - Ankylosing spondylitis
KW  - C-reactive protein
KW  - Cardiovascular risk
KW  - Machine learning
KW  - ROC curve
KW  - Random forest
KW  - Support vector machine
KW  - Spondylitis, ankylosing
KW  - C-reactive protein
KW  - Calibration
KW  - Algorithms
KW  - Machine learning
KW  - Hypertension
TI  - Cardiovascular Risk Prediction in Ankylosing Spondylitis: From Traditional Scores to Machine Learning Assessment.
TY  - research article
VL  - 7
ER  -